Prof. Mostaghim

Prof. Dr.-Ing. habil. Sanaz Mostaghim

Fakultät für Informatik (FIN)
Institut für Intelligente Kooperierende Systeme (IKS)
Universitätsplatz 2, 39106 Magdeburg, G29-008
Projekte

Aktuelle Projekte

WSAM: Wide Synthetic Aperture Sampling for Motion Classification
Laufzeit: 01.06.2023 bis 31.05.2026

We will collaborate with the Johannes Kepler University in Linz and the German Aerospace Center (DLR) in Oberpfaffenhofen. The goal of the project is the use of autonomous drone swarms for rescue applications. Here, drones can imitate the swarming behavior of birds to always have an optimal view for rescue purposes.

Considering the current high level of attention that is being paid to drones, it is easy to overlook the enormous potential that they bring with them in civilian areas. Drone groups are establishing themselves worldwide in blue light organizations such as the police, fire brigade and mountain rescue to use this technology to save human lives. Search and rescue operations benefit, among other things, from the flexible, fast and - compared to helicopters - inexpensive and safe use of drones. They are also used in the inspection of disaster areas, for the early detection of forest fires, for border security, or wildlife observation. The problem with all these applications is always the occlusion caused by vegetation, such as forest, which usually makes it impossible to find, detect, and track people, animals or vehicles in single aerial photographs. This project is based on the "Airborne Optical Sectioning" (AOS) imaging method developed at the Johannes Kepler University and will study further potentials of the swarms.

Projekt im Forschungsportal ansehen

Optimierung des Betriebs von Wirbelschichtverfahren mittels maschinellen Lernens
Laufzeit: 01.10.2022 bis 30.09.2025

Fluidized beds are the basis for scores of applications in which fast mixing, heat and mass transfer of gas and solid particles are essential. Their performance largely relies on the bubble dynamics: rising bubbles drive the solids circulation and significantly enhance gas-solids contact, improving mixing, reactions, and transport properties. So far, almost all fluidized beds are operated with a uniform gas flow. However, some recent academic work shows that operating a fluidized bed with an alternating gas flow (e.g. sinusoidal gas fluidisation velocity) leads to different bubble patterns and dynamics. In this project, we aim to control the bubbles in a fluidized bed, by application of computational intelligence (CI) methodologies such as evolutionary algorithms and genetic programming. We will use our lab-scale fluidized bed with camera system and our model developments in the Eulerian-Eulerian and Eulerian-Lagrangian frameworks to capture the dynamics of bubbles in the fluidized bed as the fluidizing gas velocity is spatio-temporally varied. Firstly, these results will be used to find the optimal inflow-pattern for given target functions. The challenge for the CI algorithm is to find the right balance between the computationally and timely intensive experimental data and the simulation data to efficiently deliver the required fluidization velocity profile. In addition, we aim to address multiple conflicting target functions using multi-objective optimization algorithms. Secondly, the CI algorithm will be used to steer and control the velocity profile, to obtain a specified bubble size and dynamics. Being able to control the behavior of the bubbles in a fluidized bed will significantly improve the desired outcome, such as product quality, efficiency and selectivity of the process, to name a few.

Projekt im Forschungsportal ansehen

BMBF - 6G-ANNA: 6G Access, Network of Networks, Automation
Laufzeit: 01.07.2022 bis 31.07.2025

In 6G-ANNA-MOEVE werden wir multi-kriterielle Optimierung und Entscheidungsfindungsalgorithmen sowie Methoden fu¨r verteiltes Lernen entwickeln. Die multi-kriteriellen Optimierungsprobleme haben mehrere Zielfunktionen, die gleichzeitig optimiert werden mu¨ssen. Ein Beispiel fu¨r solche hochkomplexe Probleme ist die Minimierung des Energieverbrauchs im Netz bei gleichzeitiger Sicherstellung von Ende- zu-Ende Performanz (Durchsatz, Latenz und Zuverla¨ssigkeit). Die Lo¨sung solcher Probleme ist eine Menge optimaler Alternativen, auf dieser Entscheidungsgrundlage kann der Anwender gema¨ß seinen Pra¨ferenzen die fu¨r ihn beste Lo¨sung auswa¨hlen. Das gibt dem Anwender ein hohes Maß an Flexibilita¨t in der Entscheidung, was zur Nachhaltigkeit der Lo¨sungen beitra¨gt.
Fu¨r eine Echtzeitoptimierung werden wir digitale Zwillinge (Simulationen) entwickeln. Allerdings spiegeln Simulationen die Realita¨t nicht perfekt wider. Daher sollen hier Methoden entwickelt werden, die eine effiziente Kombination von Offline- (Simulationsbasierte-) und Echtzeitoptimierung bieten. Eine mo¨gliche Lo¨sung fu¨r Echtzeitoptimierung kann durch verteilte Optimierung auf lokaler Ebene stattfinden. Parallelisierung bzw. die dezentrale Ausfu¨hrung von Optimierungsalgorithmen ist ein komplexes Problem und hat viele Herausforderungen, u.a. Konvergenz zu lokalem Optimum und Mobilita¨t der Knoten.
Bei der Entwicklung der Entscheidungsfindungsalgorithmen werden wir den Anwender in den Vordergrund stellen und dabei eine technische Unterstu¨tzung durch KI-Algorithmen anbieten. Ein Ziel des Projekts ist, dass durch die Interaktion zwischen Menschen und Maschine die nicht maschinenlesbaren Pra¨ferenzen der Anwender von Algorithmen verstanden werden, was wir "reverse explainability" von Entscheidungsfindung nennen. Diese findet in "Collaborative Spaces" Anwendung, die sich auf die Mensch-Maschine Interaktion, z.B. die Zusammenarbeit von Robotern und Menschen in der industriellen Produktion, fokussieren.

Projekt im Forschungsportal ansehen

Data sciEnce and Computational mODEling Platform (DECODE Platform)
Laufzeit: 01.10.2022 bis 31.12.2024

This platform is part of the projects funded by the ministry to prepare for the excellence initiative Cognitive Vitality.
The problems in cognitive vitality are so complex, that out-of-the-box Machine Learning (ML) and data science algorithms cannot be applied. Recent advances in data-driven learning, including methodologies of computational intelligence (CI), machine learning (ML) and data science, together with powerful computing resources have opened boundaries to solve real-world problems of complex systems. More than ever, we can unleash the potential of such methodologies for problems in various disciplines which had limited connection to computer science. The main goal of DECODE platform is to promote and disseminate cross-sectional research for Cognitive Vitality.

Projekt im Forschungsportal ansehen

Evolutionäre multikriterielle Optimierung
Laufzeit: 01.02.2015 bis 31.12.2024

Zentrales Thema dieses Projekts ist die Entwickelung naturinspirierter Optimierungsverfahren, insbesondere für multikriterielle und dynamisch veränderliche Problemstellungen. Wir untersuchen Mechanismen der Schwarmintelligenz und überprüfen sie auf Anwendbarkeit in technischen Systemen und mathematischen Optimierungen. Optimierungsprobleme, bei denen mehrere im Konflikt stehende Kriterien berücksichtigt werden müssen, treten zum Beispiel in vielen Anwendungen von Industrie und Wissenschaft auf. Wir untersuchen Particle Swarm Optimierungsverfahren (PSO) und evolutionäre multikriterielle Algorithmen (EMO), um multikriterielle Probleme zu lösen.

Projekt im Forschungsportal ansehen

Optimization of Modern Facility Layout Planning
Laufzeit: 01.01.2022 bis 31.12.2024

Facility layout planning and job-shop scheduling are central optimization problems for the efficiency of modern manufacturing systems. In the context of industry 4.0, these systems are often characterized by conflicting objectives, unstable demand, short product life cycles, and mass customization. Traditional facility layout planning methods are not well suited to such environments, as they ignore the contained dynamic and flexible scheduling problem. As a solution, we develop a novel simulation-based multi-objective optimization methodology that integrates facility layout planning with job-shop scheduling.

Projekt im Forschungsportal ansehen

Schwarmrobotik mit Flying Robots
Laufzeit: 01.04.2015 bis 31.12.2024

Im Rahmen dieses Projekt wird ein Roboterlabor für zunächst einen Schwarm fliegender Roboter aufgebaut. In der Schwarmrobotik werden mehrere kleine Roboter so programmiert, dass ein globales und vordefiniertes Verhalten entsteht. Solche Robotersysteme kommen schon heute in vielen Gebieten zum Einsatz. So werden im Katastrophenschutz Gruppen von mobilen Robotern zum Auffinden eines gemeinsamen Ziels beispielsweise zu Bergungszwecken oder zur Datensammlung in Katastrophengebieten genutzt. Derartige Anwendungen werden mit zunehmendem Interesse wissenschaftlich untersucht. Die Kontrolle eines solchen Schwarms von Robotern ist allerdings eine große Herausforderung und bietet eine Vielzahl an interessanten Forschungsthemen. Die Validierung der Interaktionen in Roboterschwärmen ist gegenwärtig eine der größten Herausforderung dieses Forschungsgebiets. Die Untersuchungen zeigen, dass die Umgebung und die Technik die Funktionalität der Roboter stark beeinflussen. Daher besteht der Bedarf an Experimenten, um die Methodik unter Echtzeitbedingungen zu untersuchen und weiterzuentwickeln. Damit kann eine Umwelt (Labor) von Sensoren, Robotern und mobilen Endgeräten eingerichtet und die Kommunikation und Vernetzungen untersucht werden, die die Zukunft der Anwendung solcher technischen Systeme im Alltag darstellt und simuliert.

Projekt im Forschungsportal ansehen

Traceability in Evolutionary Algorithms
Laufzeit: 01.01.2021 bis 31.12.2024

This PhD project aims to understand the traceability in evolutionary algorithms. Our goal is to introduce a methodology to trace the influence of the initial population of an evolutionary algorithm to the final population. The major challenge concerns tracking the heritage of multiple operators.

Projekt im Forschungsportal ansehen

Improving simulations of large-scale dense particle-laden flows with ma- chine learning: a genetic programming approach
Laufzeit: 15.10.2021 bis 15.10.2024

Particle-laden flows are encountered in many natural and industrial processes, such as, for instance, the flow of red and white blood cells in plasma, or the fluidization of biomass particles in furnaces. Over the last 40 years, scientists have used Euler-Lagrange (EL) simulations as a way to predict the behavior of such flows. However, EL simulations rely on models to describe the interaction between the fluid and the individually tracked particles. These models require the so-called "undisturbed” fluid velocity at the location of the particle, which is what the velocity of the fluid would have been if the particle had not been there. Current models for this are very rudimentary and precisely calculating the undisturbed fluid velocity is extremely expensive, as it would involve running many additional highly resolved simulations of the same case where one particle is left out.

This is a project to deliver a novel model for the undisturbed fluid velocity at each particle location, given the properties of the flow around the particle and of the surrounding particles, using a supervised learning machine learning approach: genetic programming (GP). GP is highly suitable, as its result will not be a "black-box” model, but a verifiable expression for the undisturbed velocity. This expression will be validated by analytical solutions and highly resolved simulations, and will enable accurate, large-scale simulations of dense particle-laden flows, while only requiring a fraction of the cost of fully resolved simulations.

Projekt im Forschungsportal ansehen

Multi-objective Optimization for Circular Supply Chain
Laufzeit: 01.05.2023 bis 30.06.2024

Im Projekt SmartProSys geht es um die Entwicklung einer smarten und nachhaltigeren Chemieindustrie durch Kreislaufwirtschaft. Die Idee, die Rohstoffe der Produkte am Ende ihres Lebenszyklus wieder in die Produktion zurückzuführen, ist angesichts des wachsenden Bedarfs an nachhaltigeren Produktionsmethoden und Ressourcennutzung vielversprechend. Im Vergleich zu traditionellen, meist linearen Produktionsprozessen, ergeben sich neue Herausforderungen, die oft ein Kompromiss zwischen den Zielen der Wirtschaftlichkeit und der Nutzung von recycelten Rohstoffen bedeuten. Multikriterielle Optimierungsverfahren eignen sich für solche Probleme, da sie Lösungen finden können, welche mehrere Ziele optimal abwägen. Wir betrachten dabei vor allem die Aspekte der Produktionsplanung und Materialbeschaffung unter den Aspekten der Wirtschaftlichkeit und Nachhaltigkeit. Die größte Herausforderung bei der Optimierung von Lieferketten hin zu zirkulären Produktionsprozessen ist eine große Menge an Parametern, die sich gegenseitig unterschiedlich beeinflussen. Wir entwickeln daher Multikriterielle Verfahren, welche in diesen komplexen Umgebungen sowohl wirtschaftliche Ziele als auch die nachhaltige Nutzung von Ressourcen optimieren.

Projekt im Forschungsportal ansehen

Abgeschlossene Projekte

Collective Decision-Making Algorithms
Laufzeit: 01.01.2020 bis 31.12.2023

Collective decision making has been a longstanding topic of study within swarm intelligence. The aim of this research area is to explain how groups of natural intelligent agents make decisions together, as well as to construct decision-making strategies that enable groups of artificial intelligent agents to come to a decision. The problems being investigated usually require the agents to form a collective decision using only their individual information and local interaction with their peers. There are two categories of problems that are primarily investigated within collective decision making, consensus achievement and task allocation. In the former category, agents need to form a singular opinion, while in the latter category, agents need to be allocated to different tasks.
In our research, we address the problem of collective perception, which is a discrete consensus achievement problem. We develop novel algorithms to deal with this problem

Projekt im Forschungsportal ansehen

Computational Intelligence in Industrial Applications
Laufzeit: 01.01.2016 bis 31.12.2023

We have two projects together with Volkswagen on the methodologies of computational intelligence in engineering and industrial contexts. We work on optimisation methods, evolutionary algorithms and neural networks to deal with various problems in automotive industry.

Projekt im Forschungsportal ansehen

Computational Intelligence in Games
Laufzeit: 01.01.2019 bis 31.12.2022

In the last decade, many commercial video games have used planners instead of classical Behavior Trees or Finite State Machines to define agent behaviors. Planners allow looking ahead in time and can prevent some problems of purely reactive systems. Furthermore, some of them allow coordination of multiple agents. However, implementing a planner for highly-dynamic environments like video games is a difficult task. This work aims to provide an overview of different elements of planners and the problems that developers might have when dealing with them. We identify the major areas of plan creation and execution, trying to guide developers through the process of implementing a planner and discuss possible solutions for problems that may arise in the following areas: environment, planning domain, goals, agents, actions, plan creation and plan execution processes. Giving insights into multiple commercial games, we show different possibilities of solving such problems and discuss which solutions are better suited under specific circumstances and why some academic approaches find a limited application in the context of commercial titles.

Projekt im Forschungsportal ansehen

MOSAIK: Methodik zur selbstorganisierten Aggregation interaktiver Komponenten
Laufzeit: 01.05.2019 bis 30.07.2022

Ziel des Vorhabens MOSAIK ist die Erforschung von Methoden, welche die flexible Zusammenarbeit von Softwarekomponenten erlauben. Die so entstehenden Aggregate sollen vorgegebene Eigenschaften erfüllen bzw. definierte Phänomene erzeugen. Zur Laufzeit sollen sich die Aggregate auf dynamisch veränderliche Umstände anpassen und somit resilient gegenüber Perturbationen sein. Neben der Erforschung der Methodik sind die weiteren Ziele von MOSAIK die Entwicklung einer Laufzeitumgebung als Open Source sowie deren prototypischer Einsatz in der industriellen Praxis.

Projekt im Forschungsportal ansehen

DORIOT: Dynamische Laufzeitumgebung für organisch (dis-)aggregierende IoT-Prozesse
Laufzeit: 01.05.2019 bis 30.06.2022

DORIOT: Dynamische Laufzeitumgebung für organisch (dis-)aggregierende IoT-Prozesse:
Das Ziel von DORIOT ist die Nutzung von Organic Computing-Ansätzen zur frühzeitigen Erkennung von Störungen und Ausfällen und zur Ergreifung von Gegenmaßnahmen für die intelligente Vernetzung der SmartX-Knoten im IoT.

Projekt im Forschungsportal ansehen

Collective Decision Making in Dynamic Environments
Laufzeit: 01.01.2019 bis 31.12.2021

In this project, we work on methods of Collective Search using Swarm Intelligence in dynamic environments. We have modelled the dynamics using Vector Fields and develop collective search methods which additionally consider these dynamics. As the dynamic are unknown, the challenge concerns the estimation and prediction of the local dynamics and their influence on the energy consumption and the search. We also work on the decision making methods for single individuals using multi-criteria decision making approaches to overcome the negative effects of the dynamics on the movement and the energy consumption.

Projekt im Forschungsportal ansehen

AI to the Rescue: Life-and-Death Decision-Making under Conflicting Criteria
Laufzeit: 01.01.2020 bis 30.09.2021

During major natural or man-made disasters, inadequate decisions on the supply of food, water,energy, shelters, medical and mental care, could have devastating impacts. In such events, "life and-death" decisions are made under time constraints, dynamic conditions, conflicting expectations, incomplete and uncertain information, infrastructure failures and insufficient resources to meet all urgent
needs. Modern technologies enable the development of dedicated AI-based Decision-Support-Systems (DSS) for such abnormal conditions. Yet, the required decisions often involve conflicting and incomparable criteria (e.g. cost versus human survival and well-being). This raises questions concerning the rationalizability, subjectivity and ethical considerations of the involved decisions. Moreover, there is a need to investigate the levels-of trust in utilizing such AI-based systems. To explore the key socio-technical aspects of "AI to the Rescue", this project will rely on experienced decision- and policy- makers,
as-well-as researchers from engineering, social and medical sciences. The envisioned research will focus on decisions concerning emergent medical operations during major disasters. The consortium will provide fresh ideas on the required AI-based DSS, in view of the unveiled socio-technical aspects.

Projekt im Forschungsportal ansehen

Swarm Intelligence in Dynamic Environments
Laufzeit: 01.10.2016 bis 30.09.2019

In this project, we work on methods of Collective Search using Swarm Intelligence in dynamic environments. We have modelled the dynamics using Vector Fields and develop collective search methods which additionally consider these dynamics. As the dynamic are unknown, the challenge concerns the estimation and prediction of the local dynamics and their influence on the energy consumption and the search. We also work on the decision making methods for single individuals using multi-criteria decision making approaches to overcome the negative effects of the dynamics on the movement and the energy consumption.

Projekt im Forschungsportal ansehen

Computational Intelligence in Games
Laufzeit: 01.01.2016 bis 01.01.2019

In the last decade, many commercial video games have used planners instead of classical Behavior Trees or Finite State Machines to define agent behaviors. Planners allow looking ahead in time and can prevent some problems of purely reactive systems. Furthermore, some of them allow coordination of multiple agents. However, implementing a planner for highly-dynamic environments like video games is a difficult task. This work aims to provide an overview of different elements of planners and the problems that developers might have when dealing with them. We identify the major areas of plan creation and execution, trying to guide developers through the process of implementing a planner and discuss possible solutions for problems that may arise in the following areas: environment, planning domain, goals, agents, actions, plan creation and plan execution processes. Giving insights into multiple commercial games, we show different possibilities of solving such problems and discuss which solutions are better suited under specific circumstances and why some academic approaches find a limited application in the context of commercial titles.

Projekt im Forschungsportal ansehen

DAAD German Australia Research Kooperation
Laufzeit: 01.01.2017 bis 31.12.2018

Optimization in presence of multiple conflicting criteria is a problem encountered in several practical domains such as engineering design, scheduling, logistics, finance etc. Such problems are called multi-objective optimization problems (MOP), and their optimum comprises not one but a set of best trade-off solutions known as the Pareto optimal front (POF). There are two key pursuits in solving MOP - first is to search for the POF, and second is to effectively choose design(s) from the POF for implementation. Both these aspects are particularly intractable and computationally prohibitive if the number of objectives is more than three. The existing methods to solve MOP are so called decomposition based evolutionary algorithms (DBEA), which try to solve it by evolving a population of solutions along a pre-defined set of reference vectors. However, defining this set of reference vectors is the biggest challenge for contemporary DBEAs. This project aims to resolve this issue by developing means to quantitatively identify solutions of interest during the search and use them to construct guiding reference vectors for the algorithm. This will enable search for high quality solutions with low computational expense, while also aiding decision making. These two aspects will make the algorithm viable for industrial use.

Projekt im Forschungsportal ansehen

Gender × Informatik., Förderung von Vernetzung und Dialog in der Forschung.
Laufzeit: 01.03.2016 bis 31.05.2018

Rasante Entwicklungen in der IT-Branche sowie deren vielfältige Auswirkungen auf die menschliche Lebenswelt erfordern zunehmend eine Beschäftigung mit nutzergerechten Gestaltungselementen. Das Zentrum für Chancengleichheit in Wissenschaft und Forschung an der TU Chemnitz hat dieses Thema aufgegriffen und ein Projekt entwickelt, das Informatikforschende für Gender und Diversity sensibilisiert und sie dabei unterstützt, Genderaspekte in den wissenschaftlichen Forschungsprozess zu integrieren und in eigenen Projekten bewusst aufzugreifen und zu reflektieren.
Die Kooperationspartner sind TU Bergakademie FreibergTU Ilmenau und OVGU Magdeburg. Die Projektdauer erstreckt sich bis Mai 2018. Das Projekt hat zum Ziel, den intensiven Dialog, die Sensibilisierung von Forschenden sowie eine verbesserte Forschungsvernetzung zwischen den Hochschulen und den Mitarbeitenden zu bewirken, um ihnen die möglichen Potentiale und Chancen der Integration von Genderaspekten in der Informatikforschung aufzuzeigen. 
Zu den Maßnahmen, um die genannte Zielsetzung zu erreichen, gehören die Durchführung einer Auftakt- sowie Abschlusstagung sowie vier thematische Workshops, in denen die Teilnehmenden ausgewählte Inputs zum Projekt erhalten und begleitend dazu fachlich und methodisch weitergebildet werden.

Projekt im Forschungsportal ansehen

Computational Intelligence in Games
Laufzeit: 01.01.2014 bis 31.12.2016

In diesem Projekt arbeiten wir an den Computational Intelligence Algorithmen; insbesondere mit evolutionären Algorithmen in Computerspielen. Unseren Schwerpunkt legen wir auf zwei Computerspiele: Multi-Objective Physical Traveling Salesman Problem und auf General Video Games. Wir entwickeln eine Vielzahl evolutionärer Algorithmen, welche in den Computerspielen integriert werden. Des Weiteren wurden Algorithmen entwickelt, um zu lernen und Entscheidungen während des Spiels zu treffen.

Projekt im Forschungsportal ansehen

Publikationen

2023

Buchbeitrag

MACO - a real-world inspired benchmark for multi-objective evolutionary algorithms

Mai, Sebastian; Benecke, Tobias; Mostaghim, Sanaz

In: Evolutionary Multi-Criterion Optimization , 1st ed. 2023. - Cham : Springer Nature Switzerland ; Emmerich, Michael, S. 305-318 - ( Lecture notes in computer science; volume 13970)

Buchbeitrag

Multi-objective multiplexer decision making benchmark problem

Djartov, Boris; Mostaghim, Sanaz

In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 1676-1683

Buchbeitrag

Multi-objective seed curve optimization for coverage path planning in precision farming

Borstelmann-Arp, Lukas; Steup, Christoph; Mostaghim, Sanaz

In: Proceedings of the Genetic and Evolutionary Computation Conference Companion - New York, NY, United States : Association for Computing Machinery . - 2023, S. 1312-1320

Buchbeitrag

Linking field decomposition and coverage path planning - a coevolution approach

Bostelmann-Arp, Lukas; Steup, Christoph; Mostaghim, Sanaz

In: IEEE CAI 2023 - Los Alamitos : IEEE, S. 294-295

Buchbeitrag

Graph networks as inductive bias for genetic programming - symbolic models for particle-laden flows

Reuter, Julia; Elmestikawy, Hani; Evrad, Fabien; Mostaghim, Sanaz; Wachem, Berend

In: Genetic Programming , 1st ed. 2023. - Cham : Springer Nature Switzerland ; Pappa, Gisele, S. 36-51 - (Lecture notes in computer science; volume 13986) [Konferenz: 26th European Conference on Genetic Programming, EuroGP 2023, Brno, Czech Republic, April 12-14, 2023]

Buchbeitrag

Online learning hyper-heuristics in multi-objective evolutionary algorithms

Heise, Julia; Mostaghim, Sanaz

In: Evolutionary Multi-Criterion Optimization , 1st ed. 2023. - Cham : Springer Nature Switzerland ; Emmerich, Michael, S. 162-175 - ( Lecture notes in computer science; volume 13970)

Buchbeitrag

Surrogate functions and digital twin simulation for modern facility layout planning

Seidelmann, Thomas; Mostaghim, Sanaz

In: IEEE CAI 2023 - Los Alamitos : IEEE, S. 197-198

Buchbeitrag

Towards a new model for a 6G network-of-networks

Rothkötter, Markus; Weise, Jens; Mostaghim, Sanaz

In: IEEE CAI 2023 - Los Alamitos : IEEE, S. 255-256

Buchbeitrag

A preference-based activity scheduling algorithm using many-objective optimization

Rothkötter, Markus; Mostaghim, Sanaz

In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 407-410

Buchbeitrag

Unfolding the variability of clinical data in Parkinson treatment using multi-objective analysis

Mostaghim, Sanaz; Shan, Qihao; Desel, Christiane Anna-Elisabeth; Duscha, Alexander; Haghikia, Aiden; Hegelmaier, Tobias Sebastian

In: IEEE CAI 2023 - Los Alamitos : IEEE, S. 120-121

Buchbeitrag

Medical and behavioral knowledge discovery using multi-objective analysis

Mostaghim, Sanaz; Shan, Qihao; Desel, Christiane Anna-Elisabeth; Duscha, Alexander; Haghikia, Aiden; Hegelmaier, Tobias Sebastian; Kuhn, Felix; Remy, Stefan

In: 2023 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) - Piscataway, NJ : IEEE, insges. 8 S.

Buchbeitrag

Effects of optimal genetic material in the initial population of evolutionary algorithms

Benecke, Tobias; Mostaghim, Sanaz

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI) - Piscataway, NJ : IEEE, S. 1386-1391

Buchbeitrag

Multi-objective Island model genetic programming for predicting the stokes flow around a sphere

Reuter, Julia; Pandey, Pravin; Mostaghim, Sanaz

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI) - Piscataway, NJ : IEEE, S. 1485-1490

Buchbeitrag

A coevolution approach for the multi-objective dircular supply chain problem

Benecke, Tobias; Antons, Oliver; Mostaghim, Sanaz; Arlinghaus, Julia C.

In: IEEE CAI 2023 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 222-223 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]

Buchbeitrag

A generalized circular supply chain problem for multi-objective evolutionary algorithms

Benecke, Tobias; Antons, Oliver; Mostaghim, Sanaz; Arlinghaus, Julia C.

In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 355-358 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]

Buchbeitrag

Towards benchmarking of pathfinding algorithms in path-influenced environments

Heise, Julia; Weise, Jens; Mostaghim, Sanaz

In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 69-70

Begutachteter Zeitschriftenartikel

Survey on multi-objective task allocation algorithms for IoT networks

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: Sensors - Basel : MDPI, Bd. 23 (2023), Heft 1, Artikel 142, insges. 23 S.

Begutachteter Zeitschriftenartikel

Evolutionary algorithm for parameter optimization of context steering agents

Dockhorn, Alexander; Kirst, Martin; Mostaghim, Sanaz; Wieczorek, Martin; Zille, Heiner

In: IEEE transactions on games - New York, NY : IEEE, Bd. 15 (2023), Heft 1, S. 26-35

Begutachteter Zeitschriftenartikel

Dynamic optimization of role concepts for role-based access control using evolutionary algorithms

Anderer, Simon; Kempter, Tobias; Scheuermann, Bernd; Mostaghim, Sanaz

In: SN Computer Science - Singapore : Springer Singapore, Bd. 4 (2023), Artikel 416, insges. 17 S.

Begutachteter Zeitschriftenartikel

Landscape analysis of multi-objective control of fluidized beds

Jamil, Iffat; Mostaghim, Sanaz; Wachem, Berend; Chéron, Victor; Hausmann, Max

In: Proceedings of the Companion Conference on Genetic and Evolutionary Computation - New York, NY, United States : Association for Computing Machinery . - 2023, S. 1950-1955 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]

Dissertation

Role mining for industrial-strength ERP systems using evolutionary algorithms

Anderer, Simon; Mostaghim, Sanaz

In: Magdeburg: Universitätsbibliothek, Dissertation Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik 2023, 1 Online-Ressource (xxiv, 287 Seiten, 66,03 MB) [Literaturverzeichnis: Seite 221-229]

Dissertation

Evolutionary many-objective optimisation for pathfinding problems

Weise, Jens; Mostaghim, Sanaz

In: Magdeburg: Universitätsbibliothek, Dissertation Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik 2023, 1 Online-Ressource (XIV, 130, XVII-CXI Seiten, 18,9 MB) [Literaturverzeichnis: Seite XVII-XXXVI]

2022

Buchbeitrag

Collective decision-making for conflict resolution in multi-agent pathfinding

Mai, Sebastian; Mostaghim, Sanaz

In: Swarm Intelligence , 1st ed. 2022. - Cham : Springer International Publishing ; Dorigo, Marco, S. 79-90 - (Lecture notes in computer science; volume 13491)

Buchbeitrag

Multi-objective roadmap optimization for multiagent navigation

Mai, Sebastian; Deubel, Maximilian; Mostaghim, Sanaz

In: Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022, 2022 IEEE Congress on Evolutionary Computation (CEC)/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE . - 2022

Buchbeitrag

Towards improving simulations of flows around spherical particles using genetic programming

Reuter, Julia; Cendrollu, Manoj; Evrard, Fabien; Mostaghim, Sanaz; Wachem, Berend

In: Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022, 2022 IEEE Congress on Evolutionary Computation (CEC)/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE . - 2022

Buchbeitrag

Surrogate models for IoT task allocation optimization

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: Konferenz: Genetic and Evolutionary Computation Conference, GECCO 22, Boston, Massachusetts, July 9 - 13, 2022, Proceedings of the Genetic and Evolutionary Computation Conference Companion - New York, NY, United States: Association for Computing Machinery; Fieldsend, Jonathan E. . - 2022, S. 364-366

Buchbeitrag

Estimating the quality of initial populations in multi-objective evolutionary algorithms

Benecke, Tobias; Mostaghim, Sanaz

In: Konferenz: Genetic and Evolutionary Computation Conference, GECCO 22, Boston, Massachusetts, July 9 - 13, 2022, Proceedings of the Genetic and Evolutionary Computation Conference Companion - New York, NY, United States: Association for Computing Machinery; Fieldsend, Jonathan E. . - 2022, S. 324-327

Buchbeitrag

Driving swarm - a swarm robotics framework for intelligent navigation in a self-organized world

Mai, Sebastian; Traichel, Nele; Mostaghim, Sanaz

In: 2022 IEEE International Conference on Robotics and Automation (ICRA)/ IEEE International Conference on Robotics and Automation - IEEE . - 2022, S. 4958-4964

Buchbeitrag

Evolutionary algorithms for the constrained two-level role mining problem

Anderer, Simon; Schrader, Falk; Scheuermann, Bernd; Mostaghim, Sanaz

In: Evolutionary Computation in Combinatorial Optimization , 1st ed. 2022. - Cham : Springer International Publishing ; Pérez Cáceres, Leslie, S. 79-94 - (Lecture notes in computer science; volume 13222)

Buchbeitrag

Genetic programming-based inverse kinematics for robotic manipulators

Reuter, Julia; Steup, Christoph; Mostaghim, Sanaz

In: Genetic Programming - Cham : Springer International Publishing ; Medvet, Eric . - 2022, S. 130-145 - ( Lecture notes in computer science; volume 13223)

Buchbeitrag

Computational intelligence methodologies for multi-objective optimization and decision-making in autonomous systems

Mostaghim, Sanaz

In: Women in Computational Intelligence , 1st ed. 2022. - Cham : Springer International Publishing ; Smith, Alice E., S. 377-392

Buchbeitrag

Benchmarking performances of collective decision-making strategies with respect to communication bandwidths in discrete collective estimation

Shan, Qihao; Mostaghim, Sanaz

In: Konferenz: 13th International Conference on Swarm Intelligence, ANTS 2022, Málaga, Spain, November 2-4, 2022, Swarm Intelligence - Cham: Springer International Publishing; Dorigo, Marco . - 2022, S. 54-65 - (Lecture notes in computer science; volume 13491)

Buchbeitrag

Multi-objective task allocation for dynamic IoT networks

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: 2022 IEEE International Conference on Omni-Layer Intelligent Systems (COINS) , 2022 - Piscataway, NJ : IEEE, insges. 5 S.

Buchbeitrag

Finding cost-effective re-layouting solutions in modern Brownfield facility layout planning

Seidelmann, Thomas; Mostaghim, Sanaz

In: Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022, 2022 IEEE Congress on Evolutionary Computation (CEC)/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE . - 2022

Begutachteter Zeitschriftenartikel

A comparison of distance metrics for the multi-objective pathfinding problem

Weise, Jens; Mostaghim, Sanaz

In: Natural computing - Dordrecht : Springer Science + Business Media B.V. . - 2022, insges. 14 S.

Begutachteter Zeitschriftenartikel

Noise-resistant and scalable collective preference learning via ranked voting in swarm robotics

Shan, Qihao; Mostaghim, Sanaz

In: Swarm intelligence - New York, NY [u.a.]: Springer . - 2022, insges. 22 S.

Begutachteter Zeitschriftenartikel

Exploring dynamic pandemic containment strategies using multi-objective Optimization [research frontier]

Fischer, Dominik; Mostaghim, Sanaz; Seidelmann, Thomas

In: IEEE computational intelligence magazine/ Institute of Electrical and Electronics Engineers - New York, NY [u.a.]: IEEE, Bd. 17 (2022), 3, S. 54-65

Begutachteter Zeitschriftenartikel

Analysis of inter and intra-front operations in multi-modal multi-objective optimization problems

Javadi, Mahrokh; Mostaghim, Sanaz

In: Natural computing - Dordrecht : Springer Science + Business Media B.V. . - 2022, insges. 16 S.

Begutachteter Zeitschriftenartikel

Availability-aware multiobjective task allocation algorithm for internet of things networks

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: IEEE internet of things journal/ Institute of Electrical and Electronics Engineers - New York, NY: IEEE, Bd. 9 (2022), 15, S. 12945-12953

Artikel in Kongressband

Multi-objective evolutionary game theory - a case study in cancer therapy

Bostelmann-Arp, Lukas; Mostaghim, Sanaz; Braun, Andreas; Tüting, Thomas

In: Konferenz: Conference on Artificial Life, ALIFE 2022, online, July 18-22, 2022, Proceedings of the Artificial Life Conference 2022, ALIFE, 2022; Holler, Silvia . - 2022, insges. 3 S.

Wissenschaftliche Monographie

Computational Intelligence - A Methodological Introduction

Kruse, Rudolf; Mostaghim, Sanaz; Borgelt, Christian; Braune, Christian; Steinbrecher, Matthias

In: Cham: Imprint: Springer, 2022., 1 Online-Ressource(XIV, 639 p. 324 illus., 42 illus. in color.) - (Texts in Computer Science; Springer eBook Collection), ISBN: 978-3-030-42227-1

2021

Buchbeitrag

The effects of crowding distance and mutation in multimodal and multi-objective optimization problems

Javadi, Mahrokh; Zille, Heiner; Mostaghim, Sanaz

In: Advances in evolutionary and deterministic methods for design, optimization and control in engineering and sciences - Cham: Springer; Gaspar-Cunha, António . - 2021, S. 115-130 - ( Computational Methods in Applied Sciences; volume 55)

Buchbeitrag

Dissecting neural networks filter responses for artistic style transfer

Uhde, Florian; Mostaghim, Sanaz

In: Konferenz: 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, Virtual Event, April 7-9, 2021, Artificial Intelligence in Music, Sound, Art and Design - Cham: Springer International Publishing; Romero, Juan . - 2021, S. 297-312 - ( Lecture notes in computer science; volume 12693)

Buchbeitrag

Mobility-aware multi-objective task allocation for wireless sensor networks

Weikert, Dominik; Steup, Christoph; Atienza, David; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 7 S.

Buchbeitrag

Discrete collective estimation in swarm robotics with ranked voting systems

Shan, Qihao; Heck, Alexander; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

A multi-objective multimodal evolutionary algorithm using a novel tournament and environmental selections

Javadi, Mahrokh; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 7 S.

Buchbeitrag

The impact of population size on the convergence of multi-objective evolutionary algorithms

Benecke, Tobias; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

Meeting demands for mass customization - a hybrid organic computing approach

Seidelmann, Thomas; Weise, Jens; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

A comparative study of different encodings on the multi-objective pathfinding problem

Weise, Jens; Zille, Heiner; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

A customized niching methodology for the many-objective pathfinding problem

Weise, Jens; Mostaghim, Sanaz

In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

Multi-objective optimization and decision-making in context steering

Dockhorn, Alexander; Mostaghim, Sanaz; Kirst, Martin; Zettwitz, Martin

In: IEEE Symposium on Computational Intelligence and Games, CIG - [Piscataway, NJ]: IEEE . - 2021, insges. 8 S.

Buchbeitrag

Enhancing resilience in IoT networks using organic computing

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: Informatik 2020 - Back to the future - Bonn : Gesellschaft für Informatik e.V. . - 2021, S. 1205-1214

Buchbeitrag

Assessment of multi-objective coevolutionary genetic programming for predicting the stokes flow around a sphere

Zille, Heiner; Evrard, Fabien; Reuter, Julia; Mostaghim, Sanaz; Wachem, Berend

In: EUROGEN 2021 - ECCOMAS Proceedia; Gauger, Nicolas . - 2021, S. 171-190

Buchbeitrag

Optimal control policies to address the pandemic health-economy dilemma

Salgotra, Rohit; Moshaiov, Amiram; Seidelmann, Thomas; Fischer, Dominik; Mostaghim, Sanaz

In: 2021 IEEE Congress on Evolutionary Computation: 28 June-1 July 2021, Kraków, Poland : 2021 proceedings - Piscataway, NJ, USA: IEEE . - 2021, S. 720-727

Buchbeitrag

Tracking the heritage of genes in evolutionary algorithms

Benecke, Tobias; Mostaghim, Sanaz

In: 2021 IEEE Congress on Evolutionary Computation: 28 June-1 July 2021, Kraków, Poland : 2021 proceedings - Piscataway, NJ, USA: IEEE . - 2021, S. 1800-1807

Buchbeitrag

Unit-aware multi-objective genetic programming for the prediction of the stokes flow around a sphere

Zille, Heiner; Mostaghim, Sanaz; Evrard, Fabien; Wachem, Berend

In: Proceedings of the Genetic and Evolutionary Computation Conference Companion/ Chicano - New York,NY,United States: Association for Computing Machinery; Chicano, Francisco . - 2021, S. 327-328

Buchbeitrag

RMPlib - a library of benchmarks for the role mining problem

Anderer, Simon; Scheuermann, Bernd; Mostaghim, Sanaz; Bauerle, Patrick; Beil, Matthias

In: Proceedings of the 26th ACM Symposium on Access Control Models and Technologies/ Lobo - New York,NY,United States: Association for Computing Machinery; Lobo, Jorge . - 2021, S. 3-13

Buchbeitrag

Many-objective pathfinding based on Fréchet similarity metric

Weise, Jens; Mostaghim, Sanaz

In: Evolutionary Multi-Criterion Optimization: 11th International Conference, EMO 2021, Shenzhen, China, March 2831, 2021, Proceedings - Cham: Springer International Publishing; Ishibuchi, Hisao - 11th International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings . - 2021, S. 375-386 - (Lecture notes in computer science; volume 12654)

Buchbeitrag

Using neighborhood-based density measures for multimodal multi-objective optimization

Javadi, Mahrokh; Mostaghim, Sanaz

In: Evolutionary Multi-Criterion Optimization: 11th International Conference, EMO 2021, Shenzhen, China, March 2831, 2021, Proceedings - Cham: Springer International Publishing; Ishibuchi, Hisao - 11th International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings . - 2021, S. 335-345 - (Lecture notes in computer science; volume 12654)

Buchbeitrag

Kooperation mittels Schwarmintelligenz

Mostaghim, Sanaz; Mai, Sebastian

In: Zusammenwirken von natürlicher und künstlicher Intelligenz - Wiesbaden: Springer VS; Haux, Reinhold *1953-* . - 2021, S. 55-69

Buchbeitrag

Combining Manhattan and crowding distances in decision space for multimodal multi-objective optimization problems

Javadi, Mahrokh; Ramirez-Atencia, Cristian; Mostaghim, Sanaz

In: Advances in evolutionary and deterministic methods for design, optimization and control in engineering and sciences - Cham: Springer; Gaspar-Cunha, António . - 2021, S. 131-145 - ( Computational Methods in Applied Sciences; volume 55)

Begutachteter Zeitschriftenartikel

A single-copter UWB-ranging-based localization system extendable to a swarm of drones

Steup, Christoph; Beckhaus, Jonathan; Mostaghim, Sanaz

In: Drones - Basel : MDPI, Bd. 5 (2021), Heft 3, Artikel 85, insges. 20 S.

Begutachteter Zeitschriftenartikel

IEEE CIS VP-member activities vision statement [society briefs]

Mostaghim, Sanaz

In: IEEE computational intelligence magazine/ Institute of Electrical and Electronics Engineers - New York, NY [u.a.]: IEEE, Bd. 16 (2021), 1, insges. 8 S.

Begutachteter Zeitschriftenartikel

Multi-featured collective perception with Evidence Theory - tackling spatial correlations

Bartashevich, Palina; Mostaghim, Sanaz

In: Swarm intelligence - New York, NY [u.a.]: Springer, Bd. 15 (2021), S. 83-110

Begutachteter Zeitschriftenartikel

Achieving task allocation in swarm intelligence with bi-objective embodied evolution

Shan, Qihao; Mostaghim, Sanaz

In: Swarm intelligence - New York, NY [u.a.] : Springer, Bd. 15 (2021), Heft 3, S. 287-310

Begutachteter Zeitschriftenartikel

A scalable many-objective pathfinding benchmark suite

Weise, Jens; Mostaghim, Sanaz

In: IEEE transactions on evolutionary computation: a publication of the IEEE Neural Networks Council/ Institute of Electrical and Electronics Engineers - New York, NY: IEEE - a publication of the IEEE Neural Networks Council . - 2021

Begutachteter Zeitschriftenartikel

Discrete collective estimation in swarm robotics with distributed Bayesian belief sharing

Shan, Qihao; Mostaghim, Sanaz

In: Swarm intelligence - New York, NY [u.a.]: Springer . - 2021, insges. 26 S.

2020

Buchbeitrag

The addRole-EA - a new evolutionary algorithm for the role mining problem

Anderer, Simon; Kreppein, Daniel; Scheuermann, Bernd; Mostaghim, Sanaz

In: Proceedings of the 12th International Joint Conference on Computational Intelligence. Volume 1: Novenber 2-4, 2020 - Scitepress Digital Library, 2020; Merelo, Juan Julian . - 2020, S. 155-166[Konferenz: 12th International Joint Conference on Computational Intelligence, web-based event, 2-4 November 2020]

Buchbeitrag

Impact of communication topology on PSO-based swarms in vector fields

Bartashevich, Palina; Koerte, Doreen; Mostaghim, Sanaz

In: 2020 IEEE Symposium Series on Computational Intelligence (SSCI)/ IEEE SSCI - [Piscataway, NJ]: IEEE . - 2020, S. 497 - 504

Buchbeitrag

Multi-objective task allocation for wireless sensor networks

Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz

In: 2020 IEEE Symposium Series on Computational Intelligence (SSCI) / IEEE SSCI , 2020 - [Piscataway, NJ] : IEEE, S. 181 - 188

Buchbeitrag

Machine learning for evaluating Kaizens in Volkswagen production system - an industrial case study

Thakur, Akshay; Beck, Robert; Mostaghim, Sanaz; Großmann, Daniel

In: 2020 IEEE International Conference on Data Science and Advanced Analytics: DSAA 2020 : 6-9 October 2020 Sydney, Australia - Piscataway, NJ: IEEE, 2020; Webb, Geoff . - 2020, S. 781-782[Konferenz: 7th International Conference on Data Science and Advanced Analytics, DSAA, Sydney, Australia, 6-9 Oct. 2020]

Buchbeitrag

Ant colony optimization based multi-robot planner for combined task allocation and path finding

Qizilbash, Agha Ali Haider; Henkel, Christian; Mostaghim, Sanaz

In: 2020 17th International Conference on Ubiquitous Robots (UR)/ International Conference on Ubiquitous Robots - [Piscataway, NJ]: IEEE, 2020 . - 2020, S. 487-493[Konferenz: 17th International Conference on Ubiquitous Robots, UR, Kyoto, Japan, 22-26 June 2020]

Buchbeitrag

T-EA - a Traceable Evolutionary Algorithm

Ramirez-Atencia, Cristian; Benecke, Tobias; Mostaghim, Sanaz

In: 2020 IEEE Congress on Evolutionary Computation (CEC): 2020 conference proceedings/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE, 2020 . - 2020, insges. 8 S.[Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]

Buchbeitrag

On the scalable multi-objective multi-agent pathfinding problem

Weise, Jens; Mai, Sebastian; Zille, Heiner; Mostaghim, Sanaz

In: 2020 IEEE Congress on Evolutionary Computation (CEC): 2020 conference proceedings/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE, 2020 . - 2020, insges. 8 S.[Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]

Buchbeitrag

A novel grid-based crowding distance for multimodal multi-objective optimization

Javadi, Mahrokh; Ramirez-Atencia, Cristian; Mostaghim, Sanaz

In: 2020 IEEE Congress on Evolutionary Computation (CEC): 2020 conference proceedings/ IEEE Congress on Evolutionary Computation - Piscataway, NJ, USA: IEEE, 2020 . - 2020, insges. 8 S.[Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]

Buchbeitrag

Survey into predictive key performance indicator analysis from data mining perspective

Thakur, Akshay; Beck, Robert; Mostaghim, Sanaz; Grosmann, Daniel

In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA): proceedings : Vienna, Austria - hybrid, 08-11 September, 2020/ IEEE International Conference on Emerging Technologies and Factory Automation - Piscataway, NJ: IEEE, 2020; IEEE International Conference on Emerging Technologies and Factory Automation (25.:2020) . - 2020, S. 476-483[Konferenz: 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, Vienna, Austria, 8-11 Sept. 2020]

Buchbeitrag

Collective decision making in swarm robotics with distributed Bayesian Hypothesis Testing

Shan, Qihao; Mostaghim, Sanaz

In: Swarm Intelligence: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020 : proceedings - Cham: Springer Nature Switzerland AG, 2020; Dorigo, Marco . - 2020, S. 55-67 - ( Lecture Notes in Computer Science; 12421)[Konferenz: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020]

Buchbeitrag

Modeling pathfinding for swarm robotics

Mai, Sebastian; Mostaghim, Sanaz

In: Swarm Intelligence: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020 : proceedings - Cham: Springer Nature Switzerland AG, 2020; Dorigo, Marco . - 2020, S. 190-202 - ( Lecture Notes in Computer Science; 12421)[Konferenz: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020]

Buchbeitrag

A many-objective route planning benchmark problem for navigation

Weise, Jens; Mostaghim, Sanaz

In: GECCO'20: proceedings of the Genetic and Evolutionary Computation Conference Companion : July 8-12, 2020, Cancún, Mexico - New York, New York: The Association for Computing Machinery, 2020 . - 2020, S. 183-184[Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '20, Cancún Mexico, 8-12 July 2020]

Begutachteter Zeitschriftenartikel

MOSAIK - a formal model for self-organizing manufacturing systems

Charpenay, Victor; Schraudner, Daniel; Seidelmann, Thomas; Spieldenner, Torsten; Weise, Jens; Schubotz, René; Mostaghim, Sanaz; Harth, Andreas

In: IEEE pervasive computing: mobile and ubiquitous systems/ Institute of Electrical and Electronics Engineers - New York, NY: IEEE . - 2020, insges. 10 S.[Online first]

Begutachteter Zeitschriftenartikel

How cognitive and environmental constraints influence the reliability of simulated animats in groups

Fischer, Dominik; Mostaghim, Sanaz; Albantakis, Larissa

In: PLOS ONE - San Francisco, California, US: PLOS, Volume 15 (2020), issue 2, article e0228879, 32 Seiten

Begutachteter Zeitschriftenartikel

Particle swarm contour search algorithm

Weikert, Dominik; Mai, Sebastian; Mostaghim, Sanaz

In: Entropy: an international and interdisciplinary journal of entropy and information studies - Basel: MDPI, Volume 22(2020), issue 4, article 407, 15 Seiten

Begutachteter Zeitschriftenartikel

Generic component-based mission-centric energy model for micro-scale unmanned aerial vehicles

Steup, Christoph; Parlow, Simon; Mai, Sebastian; Mostaghim, Sanaz

In: Drones - Basel : MDPI - Volume 4 (2020), issue 4, article 63, 17 Seiten

2019

Abstract

The effects of crowding distance and mutation in multimodal and multi-objective optimization problems

Javadi, Mahrokh; Zille, Heiner; Mostaghim, Sanaz

In: EUROGEN 2019: extended abstracts ; September 12-14, 2019, Guimarães, Portugal - Guimarães, 2019 . - 2019, S. 1-8[Konferenz: EUROGEN 2019, Guimarães, Portugal, September 12-14, 2019]

Abstract

Combining manhattan and crowding distances in decision space for multimodal multi-objective optimization problems

Javadi, Mahrokh; Ramirez-Atencia, Cristian; Mostaghim, Sanaz

In: EUROGEN 2019 - Guimarães, 2019 . - 2019, S. 1-6[Konferenz: EUROGEN 2019, Guimarães, Portugal, September 12-14, 2019]

Buchbeitrag

Multi-objective collective search and movement-based metrics in swarm robotics

Mai, Sebastian; Zille, Heiner; Steup, Christoph; Mostaghim, Sanaz

In: GECCO'19 - New York, New York : The Association for Computing Machinery ; López-Ibáñez, Manuel . - 2019, S. 387-388

Buchbeitrag

Positive impact of isomorphic changes in the environment on collective decision-making

Bartashevich, Palina; Mostaghim, Sanaz

In: GECCO'19 - New York, New York: The Association for Computing Machinery; López-Ibáñez, Manuel . - 2019, S. 105-106

Buchbeitrag

Modified crowding distance and mutation for multimodal multi-objective optimization

Javadi, Mahrokh; Zille, Heiner; Mostaghim, Sanaz

In: GECCO'19: proceedings of the Genetic and Evolutionary Computation Conference Companion : July 13-17, 2019, Prague, Czech Republic - New York, New York: The Association for Computing Machinery, 2019; López-Ibáñez, Manuel . - 2019, S. 211-212[Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]

Buchbeitrag

A local approach to forward model learning - results on the game of life game

Lucas, Simon M.; Dockhorn, Alexander; Volz, Vanessa; Bamford, Chris; Gaina, Raluca D.; Bravi, Ivan; Perez-Liebana, Diego; Mostaghim, Sanaz; Kruse, Rudolf

In: 2019 IEEE Symposium on Computational Intelligence and Games (CIG'19) - Piscataway, NJ: IEEE, 2019 . - 2019, S. 1-8[Konferenz: 2019 IEEE Conference on Games, CoG, London, United Kingdom, 20-23 August 2019]

Buchbeitrag

Benchmarking collective perception - new task difficulty metrics for collective decision-making

Bartashevich, Palina; Mostaghim, Sanaz

In: Progress in Articial Intelligence - Cham: Springer; Oliveira, Paulo Moura . - 2019, S. 699-711 - (Lecture Notes in Computer Science; vol.11805)

Buchbeitrag

Performance of dynamic algorithms on the dynamic distance minimization problem

Heibig, Mardé; Zille, Heiner; Javadi, Mahrokh; Mostaghim, Sanaz

In: GECCO'19: proceedings of the Genetic and Evolutionary Computation Conference Companion : July 13-17, 2019, Prague, Czech Republic - New York, New York: The Association for Computing Machinery, 2019; López-Ibáñez, Manuel . - 2019, S. 205-206[Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]

Buchbeitrag

Linear search mechanism for multi- and many-objective optimisation

Zille, Heiner; Mostaghim, Sanaz

In: Evolutionary multi-criterion optimization - 10th international conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019 : proceedings: 10th international conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019 : proceedings/ EMO - Cham: Springer International Publishing, 2019; Deb, Kalyanmoy . - 2019, S. 399-410 - (Lecture notes in computer science; 11411)[Konferenz: 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019]

Buchbeitrag

Ising model as a switch voting mechanism in collective perception

Bartashevich, Palina; Mostaghim, Sanaz

In: Progress in Articial Intelligence - Cham: Springer; Oliveira, Paulo Moura . - 2019, S. 617-629 - (Lecture Notes in Computer Science; vol.11805)

Buchbeitrag

Graph-based multi-objective generation of customised wiring harnesses

Weise, Jens; Benkhardt, Steven; Mostaghim, Sanaz

In: GECCO'19 - New York, New York: The Association for Computing Machinery, 2019 . - 2019, S. 407-408[Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]

Buchbeitrag

Online optimization of movement cost for robotic applications of PSO

Mai, Sebastian; Zille, Heiner; Steup, Christoph; Mostaghim, Sanaz

In: Progress in Artificial Intelligence - Cham : Springer ; Oliveira, Paulo Moura . - 2019, S. 307-318 - (Lecture Notes in Computer Science; vol.11805)

Begutachteter Zeitschriftenartikel

Building a planner - a survey of planning systems used in commercial video games

Neufeld, Xenija; Mostaghim, Sanaz; Sancho-Pradel, Dario; Brand, Sandy

In: IEEE transactions on games - New York, NY: IEEE, Bd. 11 (2019), 2, S. 91-108

Herausgeberschaft

Evolutionary multi-criterion optimization - 10th international conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019 : proceedings

Deb, Kalyanmoy; Goodman, Erik; Coello Coello, Carlos A.; Klamroth, Kathrin; Miettinen, Kaisa; Mostaghim, Sanaz; Reed, Patrick

In: Cham: Springer International Publishing, 2019, Online-Ressource (XX, 757 Seiten) - (SpringerLink; Bücher; Springer eBook Collection; Theoretical Computer Science and General Issues; 11411; Lecture notes in computer science; 11411)Kongress: EMO 10 (East Lansing, Mich. : 2019.03.10-13)

2018

Abstract

Movement-based localisation for PSO-inspired search behaviour of robotic swarms

Mai, Sebastian; Steup, Christoph; Mostaghim, Sanaz

In: Konferenz: 11th International Conference on Swarm Intelligence, ANTS 2018, Rome, Italy, October 29-31, 2018, Swarm intelligence / International Conference on Swarm Intelligence , 2018 - Cham : Springer, S. 431-432 - (Lecture Notes in Computer Science; 11172)

Buchbeitrag

A survey on graph-based systems in manufacturing processes

Weise, Jens; Benkhardt, Steven; Mostaghim, Sanaz

In: 2018 SSCI proceedings: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018 - Piscataway, NJ: IEEE, S. 112-119[Konferenz: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018]

Buchbeitrag

Towards a general framework for artistic style transfer

Uhde, Florian; Mostaghim, Sanaz

In: Computational Intelligence in Music, Sound, Art and Design - Cham: Springer, 2018 . - 2018, S. 177-193 - (Lecture Notes in Computer Science; 10783)[Konferenz: 7th International Conference, EvoMUSART 2018, Parma, Italy, April 4-6, 2018]

Buchbeitrag

Comparison study of large-scale optimisation techniques on the LSMOP benchmark functions

Zille, Heiner; Mostaghim, Sanaz

In: 2017 SSCI proceedings: 2017 IEEE SSCI, Honolulu, Hawaii, UA/ IEEE Symposium Series on Computational Intelligence - Piscataway, NJ: IEEE, 2018; IEEE Symposium Series on Computational Intelligence (10.:2017) . - 2018, insges. 8 S.[Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Honolulu, Hawaii, November 27 - December 1, 2017]

Buchbeitrag

Energy-saving decision making for aerial swarms - PSO-based navigation in vector fields

Bartashevich, Palina; Koerte, Doreen; Mostaghim, Sanaz

In: 2017 SSCI proceedings/ IEEE Symposium Series on Computational Intelligence - Piscataway, NJ: IEEE; IEEE Symposium Series on Computational Intelligence (10.:2017) . - 2018, insges. 8 S.

Buchbeitrag

How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation task

Fischer, Dominik; Mostaghim, Sanaz; Albantakis, Larissa

In: Proceeding of the Genetic and Evolutionary Computation Conference - New York, NY: ACM, S. 77-84, 2018[Konferenz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15-19, 2018]

Buchbeitrag

Transfer strategies from single- to multi-objective grouping mechanisms

Sander, Frederick; Zille, Heiner; Mostaghim, Sanaz

In: Proceeding of the Genetic and Evolutionary Computation Conference - New York, NY: ACM, 2018 . - 2018, S. 729-736[Konferenz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15-19, 2018]

Buchbeitrag

Evolving PSO algorithm design in vector fields using geometric semantic GP

Bartashevich, Paulina; Bakurov, Illya; Mostaghim, Sanaz; Vanneschi, Leonardo

In: GECCO'18 companion: proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion : July 15-19, 2018, Kyoto, Japan - New York, New York: The Association for Computing Machinery, S. 262-263[Konfernz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15 - 19, 2018]

Buchbeitrag

PSO-based search rules for aerial swarms against unexplored vector fields via genetic programming

Bartashevich, Palina; Bakurov, Illya; Mostaghim, Sanaz; Vanneschi, Leonardo

In: Parallel Problem Solving from Nature PPSN XV - Cham: Springer International Publishing . - 2018, S. 41-53 - (Lecture Notes in Computer Science; 11101)

Buchbeitrag

Vector field benchmark for collective search in unknown dynamic environments

Bartashevich, Palina; Knors, Welf; Mostaghim, Sanaz

In: Swarm intelligence: 11th International Conference, ANTS 2018, Rome, Italy, October 2931, 2018 : proceedings / Marco Dorigo, Mauro Birattari, Christian Blum, Anders L. Christensen, Andreagiovanni Reina, Vito Trianni (eds.)/ International Conference on Swarm Intelligence - Cham: Springer; Dorigo, Marco . - 2018, S. 411-419 - (Lecture Notes in Computer Science; 11172)

Buchbeitrag

Simultaneous localisation and optimisation for swarm robotics

Mai, Sebastian; Steup, Christoph; Mostaghim, Sanaz

In: 2018 SSCI proceedings / IEEE Symposium Series on Computational Intelligence , 2018 - Piscataway, NJ : IEEE, S. 1998-2004

Buchbeitrag

Understanding collective decision-making in natural swarms

Hasan, Asema; Mostaghim, Sanaz

In: 2018 SSCI proceedings: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018 - Piscataway, NJ: IEEE, S. 1563-1570[Konferenz: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018]

Buchbeitrag

A robot localization framework using CNNs for object detection and pose estimation

Hoyer, Lukas; Steup, Christoph; Mostaghim, Sanaz

In: 2018 SSCI proceedings / IEEE Symposium Series on Computational Intelligence , 2018 - Piscataway, NJ : IEEE, S. 1388-1395

Buchbeitrag

Investigation of a simple distance based ranking metric for decomposition-based multi/many-objective evolutionary algorithms

Singh, Hemant Kumar; Bhattacharjee, Kalyan Shankar; Ray, Tapabrata; Mostaghim, Sanaz

In: AI 2018: advances in artificial intelligence: 31st Australasian joint conference, Wellington, New Zealand, December 11-14, 2018 : proceedings - Cham: Springer, S. 384-396 - (Lecture notes in computer science; 11320)[Konferenz: 31st Australasian joint conference on Advances in Artificial Intelligence, AI 2018, Wellington, New Zealand, December 11-14, 2018]

Begutachteter Zeitschriftenartikel

Multi-objective distance minimization problems - applications in technical systems

Mostaghim, Sanaz; Steup, Christoph; Zille, Heiner

In: Automatisierungstechnik - Berlin : De Gruyter, Bd. 66 (2018), Heft 11, S. 964-974

Artikel in Kongressband

Meta heuristics for dynamic machine scheduling - a review of research efforts and industrial requirements

Anderer, S.; Vu, T.-H.; Scheuermann, B.; Mostaghim, Sanaz

In: IJCCI 2018: 10th International Joint Conference on Computational Intelligence : Seville, Spain, September 18-20, 2018 - [Setúbal]: SCITEPRESS - Science and Technology Publications, Lda., S. 192-203[Konferenz: 10th International Joint Conference on Computational Intelligence, IJCCI 2018, Seville, Spain, September 18-20, 2018]

2017

Buchbeitrag

A knee point based evolutionary multi-objective optimization for mission planning problems

Ramirez-Atencia, Cristian; Mostaghim, Sanaz; Camacho, David

In: Proceeding of the Genetic and Evolutionary Computation Conference : Berlin, Germany, July 15 - 19, 2017 - New York, NY : ACM, S. 1216-1223 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO 2017, Berlin, Germany, 15 - 19 July, 2017]

Buchbeitrag

Energy-saving decision making for aerial swarms - PSO-based navigation in vector fields

Bartashevich, Palina; Koerte, Doreen; Mostaghim, Sanaz

In: 2017 SSCI proceedings - Piscataway, NJ: IEEE . - 2017, S. 1848-1855

Buchbeitrag

HTN fighter - planning in a highly-dynamic game

Neufeld, Xenija; Mostaghim, Sanaz; Perez-Liebana, Diego

In: 2017 9th Computer Science and Electronic Engineering Conference (CEEC): conference proceedings : 27th-29th September 2017, University of Essex, UK/ Computer Science and Electronic Engineering Conference - [Piscataway, NJ]: IEEE; Computer Science and Electronic Engineering Conference (9.:2017) . - 2017, S. 189-194

Buchbeitrag

Dynamic distance minimization problems for dynamic multi-objective optimization

Zille, Heiner; Kottenhahn, André; Mostaghim, Sanaz

In: 2017 IEEE Congress on Evolutionary Computation (CEC): proceedings : 5-8 June 2017, Donostia-San Sebastián, Spain/ IEEE Congress on Evolutionary Computation - Piscataway, NJ: IEEE, 2017; IEEE Congress on Evolutionary Computation (2017) . - 2017, S. 952-959[Kongress: 2017 IEEE Congress on Evolutionary Computation, CEC, Donostia-San Sebastián, Spain, 5-8 June, 2017]

Buchbeitrag

PSO-based search mechanism in dynamic environments - swarms in vector fields

Bartashevich, Palina; Grimaldi, Luigi; Mostaghim, Sanaz

In: 2017 IEEE Congress on Evolutionary Computation (CEC)/ IEEE Congress on Evolutionary Computation - Piscataway, NJ: IEEE; IEEE Congress on Evolutionary Computation (2017) . - 2017, S. 1263-1270

Buchbeitrag

Elitism and aggregation methods in partial redundant evolutionary swarms solving a multi-objective tasks

Moritz, Ruby; Zille, Heiner; Mostaghim, Sanaz

In: 2017 IEEE Congress on Evolutionary Computation (CEC): proceedings : 5-8 June 2017, Donostia-San Sebastián, Spain/ IEEE Congress on Evolutionary Computation - Piscataway, NJ: IEEE, 2017; IEEE Congress on Evolutionary Computation (2017) . - 2017, S. 1467-1473[Kongress: 2017 IEEE Congress on Evolutionary Computation, CEC, Donostia-San Sebastián, Spain, 5-8 June, 2017]

Buchbeitrag

Influence of dynamic environments on agent strategies

Piper, Franz; Mostaghim, Sanaz

In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI): proceedings : 6-9 December 2016, Athens, Greece - Piscataway, NJ: IEEE, insges. 8 S., 2017[Copyright 2016; Kongress: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6th - 9th December, 2016, Athens, Greece]

Buchbeitrag

Mutation operators based on variable grouping for multi-objective large-scale optimization

Zille, Heiner; Ishibuchi, Hisao; Mostaghim, Sanaz; Nojima, Yusuke

In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI): proceedings : 6-9 December 2016, Athens, Greece/ IEEE Symposium Series on Computational Intelligence - Piscataway, NJ: IEEE, 2016 . - 2017, insges. 8 S.[Copyright 2016; Kongress: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6th - 9th December, 2016, Athens, Greece]

Buchbeitrag

Energy aware particle swarm optimization as search mechanism for aerial micro-robots

Mostaghim, Sanaz; Steup, Christoph; Witt, Fabian

In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI) , 2016 - Piscataway, NJ : IEEE . - 2017, insges. 7 S.

Buchbeitrag

Towards real-time fleet-event-handling for the dynamic vehicle routing problem

Anderer, Simon; Halbich, Max; Scheuermann, Bernd; Mostaghim, Sanaz

In: Proceedings of the 9th International Joint Conference on Computational Intelligence. Volume 1 : November 1-3, 2017, Funchal, Madeira, Portugal - [Setúbal] : SCITEPRESS - Science and Technology Publications, Lda., S. 35-44 [Konferenz: 9th International Joint Conference on Computational Intelligence, IJCCI 2017, Funchal, Madeira, Portugal, November 1-3, 2017]

Buchbeitrag

Comparison study of large-scale optimisation techniques on the LSMOP benchmark functions

Zille, Heiner; Mostaghim, Sanaz

In: 2017 SSCI proceedings - Piscataway, NJ: IEEE, 2017 . - 2017, S. 2817-2824[Beitrag auf USB-Stick]

Begutachteter Zeitschriftenartikel

Heterogeneous evolutionary swarms with partial redundancy solving multi-objective tasks

Moritz, Ruby L. V.; Mostaghim, Sanaz

In: Evolutionary multi-criterion optimization : 9th international conference, EMO 2017, Münster, Germany, March 19-22, 2017 : proceedings - Cham : Springer, S. 453-468 - (Lecture notes in computer science; 10173) [Kongress: 9th International Conference Evolutionary Multi-Criterion Optimization, EMO 2017, Münster, Germany, March 19-22, 2017]

Begutachteter Zeitschriftenartikel

A framework for large-scale multi-objective optimization based on problem transformation

Zille, Heiner; Ishibuchi, Hisao; Mostaghim, Sanaz; Nojima, Yusuke

In: IEEE transactions on evolutionary computation: a publication of the IEEE Neural Networks Council/ Institute of Electrical and Electronics Engineers - New York, NY: IEEE, 1997 . - 2017, insges. 16 S.

Begutachteter Zeitschriftenartikel

Multiobjective optimization for interwoven systems

Klamroth, Kathrin; Mostaghim, Sanaz; Naujoks, Boris; Poles, Silvia; Purshouse, Robin; Rudolph, Günter; Ruzika, Stefan; Sayın, Serpil; Wiecek, Margaret M.; Yao, Xin

In: Journal of multi-criteria decision analysis - Chichester: Wiley, Bd. 24.2017, 1/2, S. 71-81

Begutachteter Zeitschriftenartikel

Solving the Bi-objective Traveling Thief Problem with multi-objective evolutionary algorithms

Blank, Julian; Deb, Kalyanmoy; Mostaghim, Sanaz

In: Evolutionary multi-criterion optimization : 9th international conference, EMO 2017, Münster, Germany, March 19-22, 2017 : proceedings - Cham : Springer, S. 46-60 - (Lecture notes in computer science; 10173) [Kongress: 9th International Conference Evolutionary Multi-Criterion Optimization, EMO 2017, Münster, Germany, March 19-22, 2017]

Herausgeberschaft

Frontiers in Computational Intelligence

Mostaghim, Sanaz; Nürnberger, Andreas; Borgelt, Christian

In: [s.l.] Springer International Publishing AG 2018, 2017, 1 Online-Ressource - (Studies in computational intelligence; 739)

2016

Buchbeitrag

Multi-objective tree search approaches for general video game playing

Perez-Liebana, Diego; Mostaghim, Sanaz; Lucas, Simon

In: IEEE World Congress on Computational Intelligence (IEEE WCCI 2016) - Piscataway, NJ: IEEE, S. 624-631[Kongress: IEEE World Congress on Computational Intelligence, IEEE WCCI 2016, Vancouver, Canada, 24 - 29 July, 2016]

Buchbeitrag

Weighted optimization framework for large-scale multi-objective optimization

Zille, Heiner; Ishibuchi, Hisao; Mostaghim, Sanaz; Nojima, Yusuke

In: Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion - New York, NY : ACM , 2016 ; Friedrich, Tobias, S. 83-84 [Kongress: 2016 on Genetic and Evolutionary Computation Conference Companion, GECCO '16, Denver, 20. - 24. July, 2016]

Buchbeitrag

The influence of heredity models on adaptability in evolutionary swarms

Moritz, Ruby; Mostaghim, Sanaz

In: Proceedings of the International Conference on Genetic and evolutionary computation conference 2016 - New York, NY: ACM, S. 37-44[Kongress: GECCO '16, 20. - 24. July 2016, Denver, USA]

Buchbeitrag

Mutation operators based on variable grouping for multi-objective large-scale optimization

Zille, Heiner; Ishibuchi, Hisao; Mostaghim, Sanaz; Nojima, Yusuke

In: The 2016 IEEE Symposium Series on Computational Intelligence : December 6th - 9th, 2016, Athens, Greece - Piscataway, NJ : IEEE , 2016, insges. 8 S. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 6-9 December, 2016]

Buchbeitrag

Energy aware particle swarm optimization as search mechanism for aerial micro-robots

Mostaghim, Sanaz; Steup, Christoph; Witt, Fabian

In: The 2016 IEEE Symposium Series on Computational Intelligence - Piscataway, NJ : IEEE, insges. 7 S.

Buchbeitrag

Influence of dynamic environments on agent strategies

Pieper, Franz; Mostaghim, Sanaz

In: The 2016 IEEE Symposium Series on Computational Intelligence: December 6th - 9th, 2016, Athens, Greece - Piscataway, NJ: IEEE, insges. 8 S.[Kongress: 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 6-9 December, 2016]

Buchbeitrag

Multi-objective fitness-proportional attraction approach with weights

Laack, Patrick; Zille, Heiner; Mostaghim, Sanaz

In: IEEE World Congress on Computational Intelligence (IEEE WCCI 2016) - Piscataway, NJ : IEEE , 2016, S. 3316-3323 [Kongress: IEEE World Congress on Computational Intelligence, IEEE WCCI 2016, Vancouver, Canada, 24 - 29 July, 2016]

Buchbeitrag

Functional brain network extraction using a genetic algorithm with a kick-out method

Harada, Kei; Tanaka, Misato; Hiwa, Satoru; Zille, Heiner; Mostaghim, Sanaz; Hiroyasu, Tomoyuki

In: IEEE World Congress on Computational Intelligence (IEEE WCCI 2016) - Piscataway, NJ : IEEE , 2016, S. 4721-4727 [Kongress: IEEE World Congress on Computational Intelligence, IEEE WCCI 2016, Vancouver, Canada, 24 - 29 July, 2016]

Begutachteter Zeitschriftenartikel

Hybrid societies - challenges and perspectives in the design of collective behavior in self-organizing systems

Hamann, Heiko; Khaluf, Yara; Botev, Jean; Divband Soorati, Mohammad; Ferrante, Eliseo; Kosak, Oliver; Montanier, Jean-Marc; Mostaghim, Sanaz; Redpath, Richard; Timmis, Jon; Veenstra, Frank; Wahby, Mostafa; Zamuda, Aleš

In: Frontiers in robotics and AI - Lausanne, Vol. 3.2016, Art. 14, insgesamt 8 S.

Dissertation

Optimierung der Kosten und Verfügbarkeit von IT-Dienstleistungen durch Lösung eines Redundanz-Allokation-Problems

Bosse, Sascha; Turowski, Klaus; Mostaghim, Sanaz

In: Magdeburg, 2016, xii, 151 Seiten, Illustrationen, 30 cm

Artikel in Kongressband

Mixed-reality simulation environment for a swarm of autonomous indoor quadcopters

Steup, Christoph; Mostaghim, Sanaz; Mäurer, Lukas; Velinov, Vladimir

In: Kongress: Rotorcraft Virtual Engineering Conference, Liverpool, 8-10 November, 2016, Rotorcraft Virtual Engineering Conference , 2016 - [London] - 2016, paper 5.17, insgesamt 11 S.

Wissenschaftliche Monographie

Computational intelligence - a methodological introduction

Kruse, Rudolf; Borgelt, Christian; Braune, Christian; Mostaghim, Sanaz; Steinbrecher, Matthias

In: 2016, Imprint: Springer, s.l., 1 Online-Ressource (XIII, 564 p. 255 illus) - (Texts in Computer Science), ISBN: 978-1-4471-7296-3

Wissenschaftliche Monographie

Computational Intelligence - A Methodological Introduction

Kruse, Rudolf; Borgelt, Christian; Braune, Christian; Mostaghim, Sanaz; Steinbrecher, Matthias

In: London: Springer, 2016, Online-Ressource (XIII, 564 p. 255 illus, online resource) - (Texts in Computer Science; SpringerLink; Bücher; Springer eBook Collection; Computer Science), ISBN: 978-1-4471-7296-3

Nicht begutachteter Zeitschriftenartikel

Evaluation platform for micro aerial indoor swarm robotics

Steup, Christoph; Mostaghim, Sanaz; Mai, Sebastian

In: Magdeburg: FIN, 2016, 13 Seiten - (Technical Report; Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik; 2016,03)

2015

Buchbeitrag

Using -dominance for Hidden and degenerated pareto-fronts

Zille, Heiner; Mostaghim, Sanaz

In: IEEE SSCI 2015 : 2015 IEEE Symposium Series on Computational Intelligence ; 7-10 December 2015, Cape Town, South Afrika - Piscataway, NJ : IEEE , 2015, S. 845-852

Buchbeitrag

Optimization of capillary source geometry for maximum pellet exit velocity in electrothermal plasma launchers

Esmond, M. J.; Mostaghim, Sanaz; Gebhart, T. E.; Winfrey, A. L.

In: 2014 IEEE 41st International Conference on Plasma Sciences (ICOPS) held with 2014 IEEE International Conference on High-Power Particle Beams (Beams): 25 - 29 May 2014, Washington DC - Piscataway, NJ: IEEE, insges. 1 S., 2015[Copyright 2014; Konferenz: 41st IEEE International Conference on Plasma Science and the 20th International Conference on High-Power Particle Beams, ICOPS/BEAMS 2014, Washington, DC, 25 - 29 May 2014]

Buchbeitrag

Investigation of electrothermal plasma pellet launcher optimization for fusion fueling

Esmond, M. J.; Mostaghim, Sanaz; Gebhart, T. E.; Winfrey, A. L.

In: 2014 IEEE 41st International Conference on Plasma Sciences (ICOPS) held with 2014 IEEE International Conference on High-Power Particle Beams (Beams): 25 - 29 May 2014, Washington DC - Piscataway, NJ: IEEE, insges. 2 S., 2015[Copyright 2014; Konferenz: 41st IEEE International Conference on Plasma Science and the 20th International Conference on High-Power Particle Beams, ICOPS/BEAMS 2014, Washington, DC, 25 - 29 May 2014]

Buchbeitrag

Procedural level generation with answer set programming for general Video Game playing

Neufeld, Xenija; Mostaghim, Sanaz; Perez-Liebana, Diego

In: 2015 7th Computer Science and Electronic Engineering Conference (CEEC): 24 - 25 Sept. 2015, University of Essex, UK, Colchester - Piscataway, NJ: IEEE . - 2015, S. 207-212Kongress: CEEC 7 (Colchester : 2015.09.24-25)

Buchbeitrag

Properties of scalable distance minimization problems using the Manhattan metric

Zille, Heiner; Mostaghim, Sanaz

In: 2015 IEEE Congress on Evolutionary Computation (CEC 2015) : Sendai, Japan, 25 - 28 May 2015 ; [proceedings] - Piscataway, NJ : IEEE , 2015, S. 2875-2882 [Kongress: IEEE Congress on Evolutionary Computation (CEC 2015), Sendai, 25-28 May 2015]

Buchbeitrag

Open loop search for general video game playing

Liebana Perez, Diego; Diskau, Jens; Hünnermund, Martin; Mostaghim, Sanaz; Lucas, Simon

In: Proceeding of the 2015 on Genetic and Evolutionary Computation Conference - New York, NY: ACM, S. 337-344

Buchbeitrag

Runtime self-integration as key challenge for mastering interwoven systems

Hähner, Jörg; Brinkschulte, Uwe; Lukowicz, Paul; Mostaghim, Sanaz; Sick, Bernhard; Tomforde, Sven

In: Proceedings of ARCS 2015: the 28th International Conference on Architecture of Computing Systems ; March 24 - 27, 2015, Porto, Portugal - IEEE, insges. 8 S.[Workshop on Self-Optimisation in Organic and Autonomic Computing Systems (SAOS15)]

Begutachteter Zeitschriftenartikel

Multiobjective Optimization for Interwoven Systems

Ishibuchi, Hisao; Klamroth, Kathrin; Mostaghim, Sanaz; Naujoks, Boris; Poles, Silvia; Purshouse, Robin; Rudolph, Günter; Ruzika, Stefan

In: Dagstuhl Reports: Dokumentationen zu Dagstuhl-Seminaren und Dagstuhl-Perspektiven-Workshops - Wadern: Schloss Dagstuhl, Bd. 5.2015, 1, S. 139-150[Dagstuhl Seminar 15031]

Begutachteter Zeitschriftenartikel

Multiobjective Monte Carlo tree search for real-time games

Perez, Diego; Mostaghim, Sanaz; Samothrakis, Spyridon; Lucas, Simon

In: IEEE transactions on computational intelligence and AI in games - New York, NY: IEEE, Bd. 7.2015, 4, S. 347 - 360

Begutachteter Zeitschriftenartikel

Confidence measure - a novel metric for robust meta-heuristic optimisation algorithms

Mirjalili, Seyedali; Lewis, Andrew; Mostaghim, Sanaz

In: Information sciences: an international journal - New York, NY: Elsevier Science Inc, Bd. 317.2015, S. 114-142

Artikel in Kongressband

Procedural level generation with answer set programming for general video game playing

Neufeld, Xenija; Mostaghim, Sanaz; Perez, Diego

In: 7th Computer Science and Electronic Engineering Conference (CEEC) - IEEE . - 2015, S. 207-212

Originalartikel in begutachteter zeitschriftenartiger Reihe

Open Loop Search for General Video Game Playing

Perez Liebana, Diego; Dieskau, Jens; Hunermund, Martin; Mostaghim, Sanaz; Lucas, Simon

In: 2015,

2014

Buchbeitrag

Archive based multi-swarm algorithm for many-objective problems

André, Britto; Mostaghim, Sanaz; Pozo, Aurora

In: 2014 Brazilian Conference on Intelligent Systems, BRACIS 2014 - Piscataway, NJ: IEEE, S. 79-84Kongress: BRACIS 2014 (São Carlos, Brazil : 2014.10.18-23)

Buchbeitrag

A review of hybrid evolutionary multiple criteria decision making methods

Purshouse, R.; Deb, K.; Mansor, M.; Mostaghim, Sanaz; Wang, R.

In: IEEE Congress on Evolutionary Computation (CEC), 2014: 6 - 11 July 2014, Beijing, China ; [part of the 2014 IEEE World Congress on Computational Intelligence (IEEE WCCI 2014)] - Piscataway, NJ: IEEE, S. 1147-1154Kongress: CEC (Beijing : 2014.07.06-11)

Begutachteter Zeitschriftenartikel

Hop count based distance estimation in mobile ad hoc networks - challenges and consequences

Merkel, Sabrina; Mostaghim, Sanaz; Schmeck, Hartmut

In: Ad hoc Networks - Amsterdam [u.a.]: Elsevier Science, Bd. 15.2014, S. 39-52

Begutachteter Zeitschriftenartikel

Self-organized swarm display

Merkel, Sabrina; Mostaghim, Sanaz; Schmeck, Hartmut

In: International Journal of Swarm Intelligence: IJSI - Genève: Inderscience Enterprises, 2014

2013

Buchbeitrag

Distributed swarm evacuation planning

Merkel, Sabrina; Mostaghim, Sanaz; Blum, D.; Schmeck, Hartmut

In: Proceedings of the 2013 IEEE Swarm Intelligence Symposium (SIS). - Piscataway, NJ : IEEE, S. 276-283

Buchbeitrag

Iterated multi-swarm: a multi-swarm algorithm based on archiving methods

Britto, Andre; Mostaghim, Sanaz; Pozo, Aurora

In: Alba, Enrique: : Proceeding of the fifteenth annual conference on Genetic and evolutionary computation conference. - New York, NY : ACM, S. 583-590, 2013Kongress: GECCO 13; 15 (Amsterdam, Netherlands) : 2013.07.06-10

Begutachteter Zeitschriftenartikel

Experimental analysis of bound handling techniques in particle swarm optimization

Helwig, Sabine; Branke, Juergen; Mostaghim, Sanaz

In: IEEE transactions on evolutionary computation. - New York, NY : IEEE, Bd. 17.2013, 2, S. 259-271

Begutachteter Zeitschriftenartikel

Preface: Nature inspired solutions for high performance computing

Folino, G.; Mastroianni, C.; Mostaghim, S.

In: Natural Computing, Vol. 12, 2013, Issue 1, S. 27-28, ISSN 15677818, 10.1007/s11047-012-9326-9

Originalartikel in begutachteter internationaler Zeitschrift

Hop Count Based Distance Estimation in Mobile Ad Hoc Networks - Challenges and Consequences

Merkel, Sabrina; Mostaghim, Sanaz; Schmeck, Hartmut

In: Journal of Ad Hoc Networks on “Smart Solutions for Mobility Supported Distributed and Embedded Systems”

Originalartikel in begutachteter zeitschriftenartiger Reihe

Multi-iterated Swarm

Britto, Andre; Mostaghim, Sanaz; Pozo, Ana

In: Genetic and Evolutionary Computation Conference (GECCO), pages 56 – 64, July 2013

Originalartikel in begutachteter zeitschriftenartiger Reihe

Identification of Success Criteria and underlying Parameters for the Evaluation of newly created Ventures

Presse, Andre; Mostaghim, Sanaz; Stroisch, Philip

In: 17th Interdisciplinary Entrepreneurship Conference, November 2013

2012

Begutachteter Zeitschriftenartikel

Distributed geometric distance estimation in ad hoc networks

Merkel, S.; Mostaghim, S.; Schmeck, H.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 7363 LNCS, 2012, S. 28-41, ISSN 03029743, 10.1007/978-3-642-31638-8_3

Begutachteter Zeitschriftenartikel

Validating a peer-to-peer evolutionary algorithm

Laredo, J.L.J.; Bouvry, P.; Mostaghim, S.; Merelo-Guervós, J.-J.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 7248 LNCS, 2012, S. 436-445, ISSN 03029743, 10.1007/978-3-642-29178-4_44

Herausgeberschaft

A study of mobility in ad hoc networks and its effects on a hop count based distance estimation

Merkel, S.; Mostaghim, S.; Schmeck, H.

In: 2012 5th International Conference on New Technologies, Mobility and Security - Proceedings of NTMS 2012 Conference and Workshops, 2012, 10.1109/NTMS.2012.6208681

Herausgeberschaft

Adaptive range parameter control

Aleti, A.; Moser, I.; Mostaghim, S.

In: 2012 IEEE Congress on Evolutionary Computation, CEC 2012, 2012, 10.1109/CEC.2012.6256567

2011

Herausgeberschaft

A Markov-chain-based model for success prediction of evolution in complex environments

König, L.; Mostaghim, S.; Schmeck, H.

In: ECTA 2011 FCTA 2011 - Proceedings of the International Conference on Evolutionary Computation Theory and Applications and International Conference on Fuzzy Computation Theory and Applications, 2011, S. 90-102

Herausgeberschaft

8th International Conference on Autonomic Computing, ICAC 2011 Co-located Workshops - Proceedings of the 3rd Workshop on Biologically Inspired Algorithms for Distributed Systems, BADS 2011: Foreword

Folino, G.; Mastroianni, C.; Mostaghim, S.; Suzuki, J.

In: 8th International Conference on Autonomic Computing, ICAC 2011 Co-located Workshops - Proceedings of the 3rd Workshop on Biologically Inspired Algorithms for Distributed Systems, BADS 2011, 2011, S. iii-iv

Herausgeberschaft

Self-organized invasive parallel optimization

Mostaghim, S.; Pfeiffer, F.; Schmeck, H.

In: 8th International Conference on Autonomic Computing, ICAC 2011 Co-located Workshops - Proceedings of the 3rd Workshop on Biologically Inspired Algorithms for Distributed Systems, BADS 2011, 2011, S. 49-56, 10.1145/1998570.1998581

2010

Begutachteter Zeitschriftenartikel

Preference-based multi-objective particle swarm optimization using desirabilities

Mostaghim, S.; Trautmann, H.; Mersmann, O.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 6239 LNCS, 2010, Issue PART 2, S. 101-110, ISSN 03029743, 10.1007/978-3-642-15871-1_11

Begutachteter Zeitschriftenartikel

Interactive multi-objective particle swarm optimization with heatmap-visualization-based user interface

Hettenhausen, J.; Lewis, A.; Mostaghim, S.

In: Engineering Optimization, Vol. 42, 2010, Issue 2, S. 119-139, ISSN 0305215X, 10.1080/03052150903042632

Begutachteter Zeitschriftenartikel

Parallel multi-objective optimization using self-organized heterogeneous resources

Mostaghim, S.

In: Studies in Computational Intelligence, Vol. 269, 2010, S. 165-179, ISSN 1860949X, 10.1007/978-3-642-10675-0_8

Herausgeberschaft

The automotive deployment problem: A practical application for constrained multiobjective evolutionary optimisation

Moser, I.; Mostaghim, S.

In: 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010, 10.1109/CEC.2010.5585991

Herausgeberschaft

Parallel optimisation and parameter fitting

Mostaghim, S.

In: Proceedings - 6th IEEE International Conference on e-Science Workshops, e-ScienceW 2010, 2010, S. xii, 10.1109/eScienceW.2010.8

Herausgeberschaft

Organic computing in off-highway machines

Wüensche, M.; Mostaghim, S.; Schmeck, H.; Kautzmann, T.; Geimer, M.

In: Proceeding of the 2nd International Workshop on Self-Organizing Architectures, SOAR '10, Co-located with ICAC'10, 2010, S. 51-58, 10.1145/1809036.1809048

2009

Begutachteter Zeitschriftenartikel

Asynchronous multi-objective optimisation in unreliable distributed environments

Lewis, A.; Mostaghim, S.; Scriven, I.

In: Studies in Computational Intelligence, Vol. 210, 2009, S. 51-78, ISSN 1860949X, 10.1007/978-3-642-01262-4_3

Begutachteter Zeitschriftenartikel

Self-organized parallel cooperation for solving optimization problems

Mostaghim, S.; Schmeck, H.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5455 LNCS, 2009, S. 135-145, ISSN 03029743, 10.1007/978-3-642-00454-4_15

Begutachteter Zeitschriftenartikel

Decentralized evolution of robotic behavior using finite state machines

König, L.; Mostaghim, S.; Schmeck, H.

In: International Journal of Intelligent Computing and Cybernetics, Vol. 2, 2009, Issue 4, S. 695-723, ISSN 1756378X, 10.1108/17563780911005845

Begutachteter Zeitschriftenartikel

Studies in Computational Intelligence: Preface

Lewis, A.; Mostaghim, S.; Randall, M.

In: Studies in Computational Intelligence, Vol. 210, 2009, S. V-IX, ISSN 1860949X

Herausgeberschaft

Online and onboard evolution of robotic behavior using finite state machines

König, L.; Mostaghim, S.; Schmeck, H.

In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, Vol. 2, 2009, S. 1158-1159, ISSN 15488403

Herausgeberschaft

Intelligent business process execution using particle swarm optimization

Kress, M.; Mostaghim, S.; Seese, D.

In: Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science, and Engineering, 2009, S. 49-66, 10.4018/978-1-60566-705-8.ch003

Herausgeberschaft

Dynamic search initialisation strategies for multi-objective optimisation in peer-to-peer networks

Scriven, I.; Lewis, A.; Mostaghim, S.

In: 2009 IEEE Congress on Evolutionary Computation, CEC 2009, 2009, S. 1515-1522, 10.1109/CEC.2009.4983122

Herausgeberschaft

Empirical comparison of MOPSO methods-guide selection and diversity preservation

Padhye, N.; Branke, J.; Mostaghim, S.

In: 2009 IEEE Congress on Evolutionary Computation, CEC 2009, 2009, S. 2516-2523, 10.1109/CEC.2009.4983257

2008

Begutachteter Zeitschriftenartikel

Parallel approaches for multiobjective optimization

Talbi, E.-G.; Mostaghim, S.; Okabe, T.; Ishibuchi, H.; Rudolph, G.; Coello Coello, C.A.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5252 LNCS, 2008, S. 349-372, ISSN 03029743, 10.1007/978-3-540-88908-3-13

Begutachteter Zeitschriftenartikel

Design of gate array circuits using evolutionary algorithms

Bungert, P.; Mostaghim, S.; Schmeck, H.; Branke, J.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 4934 LNCS, 2008, S. 38-50, ISSN 03029743, 10.1007/978-3-540-78153-0_5

Begutachteter Zeitschriftenartikel

Hybridizing evolutionary strategies with continuation methods for solving multi-objective problems

Schütze, O.; Coello, C.A.C.; Mostaghim, S.; Talbi, E.-G.; Dellnitz, M.

In: Engineering Optimization, Vol. 40, 2008, Issue 5, S. 383-402, ISSN 0305215X, 10.1080/03052150701821328

Begutachteter Zeitschriftenartikel

Distance based ranking in many-objective particle swarm optimization

Mostaghim, S.; Schmeck, H.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 5199 LNCS, 2008, S. 753-762, ISSN 03029743, 10.1007/978-3-540-87700-4_75

Herausgeberschaft

Parallel multi-objective optimization using master-slave model on heterogeneous resources

Mostaghim, S.; Branke, J.; Lewis, A.; Schmeck, H.

In: 2008 IEEE Congress on Evolutionary Computation, CEC 2008, 2008, S. 1981-1987, 10.1109/CEC.2008.4631060

Herausgeberschaft

Evolutionary population dynamics and multi-objective optimisation problems

Lewis, A.; Mostaghim, S.; Randall, M.

In: Multi-Objective Optimization in Computational Intelligence: Theory and Practice, 2008, S. 185-206, 10.4018/978-1-59904-498-9.ch007

Herausgeberschaft

Asynchronous multiple objective particle swarm optimisation in unreliable distributed environments

Scriven, I.; Ireland, D.; Lewis, A.; Mostaghim, S.; Branke, J.

In: 2008 IEEE Congress on Evolutionary Computation, CEC 2008, 2008, S. 2481-2486, 10.1109/CEC.2008.4631130

2007

Begutachteter Zeitschriftenartikel

Heatmap visualization of population based multi objective algorithms

Pryke, A.; Mostaghim, S.; Nazemi, A.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 4403 LNCS, 2007, S. 361-375, ISSN 03029743

Herausgeberschaft

Multi-objective particle swarm optimization on computer grids

Mostaghim, S.; Branke, J.; Schmeck, H.

In: Proceedings of GECCO 2007: Genetic and Evolutionary Computation Conference, 2007, S. 869-875, 10.1145/1276958.1277127

2006

Begutachteter Zeitschriftenartikel

About selecting the personal best in multi-objective particle swarm optimization

Branke, J.; Mostaghim, S.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 4193 LNCS, 2006, S. 523-532, ISSN 03029743

Begutachteter Zeitschriftenartikel

Linear multi-objective particle swarm optimization

Mostaghim, S.; Halter, W.; Wille, A.

In: Studies in Computational Intelligence, Vol. 31, 2006, S. 209-238, ISSN 1860949X, 10.1007/978-3-540-34690-6_9

Herausgeberschaft

Bilevel optimization of multi-component chemical systems using particle swarm optimization

Halter, W.; Mostaghim, S.

In: 2006 IEEE Congress on Evolutionary Computation, CEC 2006, 2006, S. 1240-1247

Herausgeberschaft

Hybrid particle guide selection methods in multi-objective particle swarm optimization

Ireland, D.; Lewis, A.; Mostaghim, S.; Lu, J.W.

In: e-Science 2006 - Second IEEE International Conference on e-Science and Grid Computing, 2006, 10.1109/E-SCIENCE.2006.261049

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Mehr im Forschungsportal ansehen.

Kooperationen
  • Prof. Dr. Simon Lucas, University of Essex, UK
  • Prof. Dr. Hisao Ishibuchi, Osaka Prefecture University, Japan
  • Tomo Hiroyasu, Doshisha University Kyoto, Japan
  • Proctor and Gamble GmbH
  • - Prof. Dr. Tomo Hiroyasu, Medical Information System Laborator(MISL) Faculty of Life and Medical Sciences, Doshisha University, Japan
  • - Dr. Andrew Lewis, Griffith University, Brisbane, Australien
  • - Prof. Dr. Kalyanmoy Deb, Michigan State University, USA
  • - Prof. Dr. Hartmut Schmeck, Karlsruher Institut für Technologie (KIT)
  • - Prof. Dr. Brian Scassellati, Yale University, USA
  • - Dr. André Presse, Karlsruher Institut für Technologie (KIT)
  • AKKA Germany GmbH
  • BOSCH GMbH
  • Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI)
  • DLR, Institut für Robotik und Mechatronik, Ober­pfaf­fen­ho­fen
  • Hochschule Bielefeld
  • Leibniz Institut für Neurobiologie Magdeburg
  • Medizinische Fakultät der Otto-von-Guericke-Universität Magdeburg
  • NETSYNO Software GmbH
  • OVGU, Fakultät für Verfahrens- und Systemtechnik Institut für Verfahrenstechnik Lehrstuhl Mechanische Verfahrenstechnik, Prof. Berend Van Wachem
  • Prof. Berend van Wachem, OVGU, Fakultät für Verfahrens- und Systemtechnik Institut für Verfahrenstechnik Lehrstuhl Mechanische Verfahrenstechnik
  • Prof. Dr. Andreas Harth, Friedrich-Alexander-Universität Erlangen-Nürnberg
  • Prof. Dr. Julia Arlinghaus (FMB)
  • Prof. Oliver Bimber, Universität Linz
  • Thorsis Technologies GmbH
Profil
    • Computational Intelligence
    • Multikriterielle Optimierungalgorithmen
    • Evolutionäre Algorithmen 
    • Multikriterielle Entscheidungsfindungalgorithmen 
    • Schwarmintelligenz
    • Schwarmrobotik
Service
Beratung, Gutachten und Projekte zu:
  • Schwarmintelligenz und Schwarmrobotik
  • Computational Intelligence
  • Multikriterielle Optimierung
Vita
Sanaz Mostaghim is a full professor of Computer Science at the Otto von Guericke University of Magdeburg, since 2014.
She received her PhD degree in electrical engineering and computer science under the supervision of Prof. Dr. Jürgen Teich at the University of Paderborn in 2004.  Sanaz joined the Computational Laboratory (CoLab) of the computational science department at the Swiss Federal Institute of Technology (ETH) Zurich in Switzerland in 2004. In 2006, Sanaz joined Institute AIFB at Karlsruhe Institute of Technology (KIT) and started working on her habilitation in applied computer science which she successfully finished in 2012. The title of her habilitation thesis is: Self-organized Parallel Optimization. 
In 2010, Sanaz was a visiting scholar at Swinburne University of Technology, Melbourne, Australia and in 2013 she has been a visiting scholar at the Yale University, New Haven, USA, where she visited the Social Robotic Laboratory.

In 2014, Sanaz received the prestigious DFG Heisenberg-Professorship at KIT.

Sanaz is an active member in international communities. She is the vice president of IEEE Computational Intelligence Society (starting from 2021) and served as adcom member for two terms (2015-2020).

Selected activities since 2019: 
  • since 2021: Vice President for member activities at IEEE Computational Intelligence Society 
  • 2021: General Chair, IEEE Symposium Series on Computational Intelligence, December 2021, Orlando, USA
  • since 2020: Member of the senate of the University of Magdeburg 
  • since 2018: Appointed as the member of the advisory board on digitalization, Ministry of Economy, Science and Digitalization, State Sachsen-Anhalt, Germany 
  • since 2016: Deputy chair and member of the executive board Informatics Germany (Fakultätentag Informatik der Bundesrepublik Deutschland)
  • since 2017: Chair of the Steering Board, IEEE Transactions on Games (ToG) 
  • since 2020: Appointed as IEEE CIS Distinguished Lecturer
  • since 2020: Associate Editor IEEE Transactions on AI 
  • since 2012: Associate Editor IEEE Transactions on Evolutionary Computation 
  • since 2020: Vertrauendozentin, Stiftung der Deutschen Wirtschaft (SDW)
  • since 2010: Member of Evolutionary Computation Technical Committee (ECTC) - IEEE Computational Intelligence Society (CIS)
  • 2015 - 2020: Elected member of Administrative Committee (ADCOM) -  IEEE Computational Intelligence Society (IEEE-CIS)  
  • 2020: Chair, Multi-Criteria Decision-Making Symposium, IEEE Symposium Series on Computational Intelligence, December 2020, Australia
  • 2020: Track Chair, Evolutionary Multi-Criteria Optimization, GECCO, July 2020, Mexico
  • 2019: Program Chair, Evolutionary Multicriterion Optimization Conference, March 2019, Michigan, USA 
  • 2019: General Chair, IEEE Conference on Games, 20-23 August 2019, London, UK
  • since 2019: Member of 4ING Board (4ING der Dachverein der Fakultätentage der Ingenieurwissenschaften und der Informatik an Universitäten).

seit 2014 

2013 -14

Universitätsprofessorin, Lehrstuhl für Computational IntelligenceInstitut für Wissens- und Sprachverarbeitung (IWS) Fakultät für Informatik Otto-von-Guericke-Universität Magdeburg

Dorothea-Erxleben-Gastprofessorin Institut für Wissens- und Sprachverarbeitung (IWS) Fakultät für Informatik Otto-von-Guericke-Universität Magdeburg

2013

Visiting Scholar Faculty of Computer Science Yale University, USA

Mai 2012

Habilitation Angewandte Informatik Karlsruher Institut für Technologie (KIT)

2009-2010

Gastwissenschaftlerin Faculty of Information and Communication Technologies Swinburne University of Technology, Melbourne, Australien

2006 - 13

Akademische Rätin auf Zeit Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB) Karlsruher Institut für Technologie (KIT)

2004 - 06

Postdoctoral Fellow Computational Laboratory (CoLab) Institute of Computational Science Department Informatik  ETH Zürich - Eidgenössische Technische Hochschule Zürich

September 2004

Promotion Fakultät für Elektrotechnik, Informatik und Mathematik (EIM) Universität Paderborn

2001 - 04

Doktorandin DFG Graduiertenkolleg - Paderborn Institute for Scientific Computation (PaSCo): Application-oriented Modelling and Development of Algorithms Fakultät für Elektrotechnik, Informatik und Mathematik (EIM) Universität Paderborn
Presse
Our major focus in research and teaching is on Intelligent Systems, particularly Computational Intelligence and Swarm Intelligence.
Computational Intelligence is an important tool for dealing with complex systems and can be used everywhere: automotive industry, medical applications, chemistry, geology, entrepreneurship, system design, games, biology, etc. In this area, we work on evolutionary algorithms, particle swarm optimization and their applications on multi-objective problems.
Furthermore, we study algorithms and different applications of Swarm Intelligence in optimization, swarm robotics, and distributed systems. Swarm Intelligence is a collective learning mechanism with the goal to achieve a global complex and intelligent behavior using simple rules on simple technical devices.
Lehrveranstaltungen

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