Prof. Mostaghim
Prof. Dr.-Ing. habil. Sanaz Mostaghim
Institut für Intelligente Kooperierende Systeme (IKS)
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.
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.
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.
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.
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.
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.
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.
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.
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.
Abgeschlossene Projekte
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 Freiberg, TU 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.
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.
2024
Buchbeitrag
Finding sets of solutions for temporal uncertain problems
Weise, Jens; Mostaghim, Sanaz
In: Applications of Evolutionary Computation - Cham : Springer Nature Switzerland ; Smith, Stephen . - 2024, S. 209-223 - ( Lecture notes in computer science; volume 14634) [Konferenz: 27th International Conference on the Applications of Evolutionary Computation, Aberystwyth, UK, April 3-5, 2024]
Unit-aware genetic programming for the development of empirical equations
Reuter, Julia; Martinek, Viktor; Herzog, Roland; Mostaghim, Sanaz
In: Parallel Problem Solving from Nature – PPSN XVIII - Cham : Springer ; Affenzeller, Michael . - 2024, S. 168-183 - ( Lecture notes in computer science; volume 15151) [Konferenz: International Conference on Parallel Problem Solving from Nature, PPSN 2024, Hagenberg, Austria, September 14–18, 2024]
Innovization for route planning applied to an Uber Movement Speeds dataset for Berlin
Röpper, Eva; Weise, Jens; Steup, Christoph; Mostaghim, Sanaz
In: Parallel Problem Solving from Nature – PPSN XVIII - Cham : Springer ; Affenzeller, Michael . - 2024, S. 100-116 - ( Lecture notes in computer science; volume 15151) [Konferenz: International Conference on Parallel Problem Solving from Nature, PPSN 2024, Hagenberg, Austria, September 14–18, 2024]
Adverse weather benchmark dataset for LiDAR-based 3D object recognition and segmentation in autonomous driving
Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz
In: 2024 IEEE Conference on Artificial Intelligence (CAI) - Piscataway, NJ : IEEE, S. 125-126 [Konferenz: 2024 IEEE Conference on Artificial Intelligence (CAI), Singapore, 25-27 June 2024]
A learning classifier system approach to time-critical decision-making in dynamic alternate airport selection
Djartov, Boris; Mostaghim, Sanaz; Papenfuß, Anne; Wies, Matthias
In: 2024 IEEE Congress on Evolutionary Computation (CEC) - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: 2024 IEEE Congress on Evolutionary Computation, CEC, Yokohama, Japan, 30 June 2024 - 05 July 2024]
Application of a bi-objective EA for RAN resources optimization in a dynamic scenario
Rothkötter, Markus; Kluge, Niklas; Mostaghim, Sanaz
In: 2024 IEEE Congress on Evolutionary Computation (CEC) - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: 2024 IEEE Congress on Evolutionary Computation, CEC, Yokohama, Japan, 30 June 2024 - 05 July 2024]
A survey on multi-objective optimization in microgrid systems
Islam, Saiful; Mostaghim, Sanaz; Hartmann, Michael
In: 2024 IEEE Congress on Evolutionary Computation (CEC) - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: 2024 IEEE Congress on Evolutionary Computation, CEC, Yokohama, Japan, 30 June 2024 - 05 July 2024]
Optimized drug design using multi-objective evolutionary algorithms with SELFIES
Hömberg, Tomoya; Mostaghim, Sanaz; Hiwa, Satoru; Hiroyasu, Tomoyuki
In: 2024 IEEE Congress on Evolutionary Computation (CEC) - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: 2024 IEEE Congress on Evolutionary Computation, CEC, Yokohama, Japan, 30 June 2024 - 05 July 2024]
Free-form coverage path planning of quadcopter swarms for search and rescue missions using multi-objective optimization
Bostelmann-Arp, Lukas; Steup, Christoph; Mostaghim, Sanaz
In: 2024 IEEE Congress on Evolutionary Computation (CEC) - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: 2024 IEEE Congress on Evolutionary Computation, CEC, Yokohama, Japan, 30 June 2024 - 05 July 2024]
Survival strategies for evolutionary role mining algorithms using expert knowledge
Anderer, Simon; Juston, Nicolas; Scheuermann, Bernd; Mostaghim, Sanaz
In: GECCO '24 Companion - New York, New York : The Association for Computing Machinery . - 2024, S. 623-626 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '24 Companion, Melbourne, Australia, July 14 - 18, 2024]
Begutachteter Zeitschriftenartikel
Many-option collective decision making - discrete collective estimation in large decision spaces
Shan, Qihan; Mostaghim, Sanaz
In: Swarm intelligence - New York, NY [u.a.] : Springer . - 2024 [Online first]
Deterministic drag modelling for spherical particles in Stokes regime using data-driven approaches
Elmestikawy, Hani; Reuter, Julia; Evrard, Fabien; Mostaghim, Sanaz; Wachem, Berend
In: International journal of multiphase flow - Oxford : Pergamon Press, Bd. 178 (2024), Artikel 104880, insges. 13 S.
2023
Buchbeitrag
Surrogate functions and digital twin simulation for modern facility layout planning
Seidelmann, Thomas; Mostaghim, Sanaz
In: IEEE CAI 2023 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 197-198 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]
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) , 2023 - Piscataway, NJ : IEEE, S. 1485-1490 [Symposium: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexiko City, 05.-08. December 2023]
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) , 2023 - Piscataway, NJ : IEEE, S. 1386-1391 [Symposium: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), Mexiko City, 05.-08. December 2023]
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) / IEEE CIBCB , 2023 - Piscataway, NJ : IEEE, insges. 8 S. [Konferenz: IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB, Eindhoven, Netherlands, 29-31 August 2023]
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 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 120-121 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]
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]
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 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]
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 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]
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
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]
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) [Konferenz: 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023]
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) [Konferenz: 12th International Conference, EMO 2023, Leiden, The Netherlands, March 20-24, 2023]
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]
Linking field decomposition and coverage path planning - a coevolution approach
Bostelmann-Arp, Lukas; Steup, Christoph; Mostaghim, Sanaz
In: IEEE CAI 2023 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 294-295 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]
Towards a new model for a 6G network-of-networks
Rothkötter, Markus; Weise, Jens; Mostaghim, Sanaz
In: IEEE CAI 2023 / IEEE Conference on Artificial Intelligence , 2023 - Los Alamitos : IEEE, S. 255-256 [Konferenz: 2023 IEEE Conference on Artificial Intelligence, CAI 2023, Santa Clara, Califonien, USA, 05-06 June 2023]
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 [Konferenz: Companion Conference on Genetic and Evolutionary Computation, GECCO '23 Companion, Lisbon, Portugal, July 15 - 19, 2023]
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]
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.
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
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.
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][Literaturverzeichnis: Seite 221-229]
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][Literaturverzeichnis: Seite XVII-XXXVI]
2022
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) [Konferenz: 25th European Conference on Genetic Programming, EuroGP 2022, Madrid, Spain, April 20-22, 2022]
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) [Konferenz: 13th International Conference on Swarm Intelligence, ANTS 2022, Málaga, Spain, November 2-4, 2022]
Benchmarking performances of collective decision-making strategies with respect to communication bandwidths in discrete collective estimation
Shan, Qihao; Mostaghim, Sanaz
In: Swarm Intelligence , 1st ed. 2022. - Cham : Springer International Publishing ; Dorigo, Marco, S. 54-65 - (Lecture notes in computer science; volume 13491) [Konferenz: 13th International Conference on Swarm Intelligence, ANTS 2022, Málaga, Spain, November 2-4, 2022]
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. [Konferenz: IEEE International Conference on Omni-layer Intelligent Systems, COINS, Barcelona, Spain, 01-03 August 2022]
Finding cost-effective re-layouting solutions in modern Brownfield facility layout planning
Seidelmann, Thomas; Mostaghim, Sanaz
In: 2022 IEEE Congress on Evolutionary Computation, CECE , 2022 - Piscataway, NJ, USA : IEEE [Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022]
Multi-objective roadmap optimization for multiagent navigation
Mai, Sebastian; Deubel, Maximilian; Mostaghim, Sanaz
In: 2022 IEEE Congress on Evolutionary Computation, CECE , 2022 - Piscataway, NJ, USA : IEEE [Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022]
Towards improving simulations of flows around spherical particles using genetic programming
Reuter, Julia; Cendrollu, Manoj; Evrard, Fabien; Mostaghim, Sanaz; Wachem, Berend
In: 2022 IEEE Congress on Evolutionary Computation, CECE , 2022 - Piscataway, NJ, USA : IEEE [Kongress: 2022 IEEE Congress on Evolutionary Computation, CEC, Padua, Italy, 18-23 July 2022]
Surrogate models for IoT task allocation optimization
Weikert, Dominik; Steup, Christoph; Mostaghim, Sanaz
In: 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 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO 22, Boston, Massachusetts, July 9 - 13, 2022]
Estimating the quality of initial populations in multi-objective evolutionary algorithms
Benecke, Tobias; Mostaghim, Sanaz
In: 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 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO 22, Boston, Massachusetts, July 9 - 13, 2022]
Driving swarm - a swarm robotics framework for intelligent navigation in a self-organized world
Mai, Sebastian; Traichel, Nele; Mostaghim, Sanaz
In: 2022 International Conference on Robotics and Automation (ICRA) / IEEE International Conference on Robotics and Automation , 2022 - IEEE, S. 4958-4964
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) [Konferenz: 22nd European Conference, EvoCOP 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 2022, 2022]
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
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), Heft 3, S. 54-65
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. [Online first]
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), Heft 15, S. 12945-12953
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. [Online first]
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. [Online first]
Artikel in Kongressband
Multi-objective evolutionary game theory - a case study in cancer therapy
Bostelmann-Arp, Lukas; Mostaghim, Sanaz; Braun, Andreas; Tüting, Thomas
In: Proceedings of the Artificial Life Conference 2022, ALIFE ; Holler, Silvia, Artikel isal_a_00498,20, insges. 3 S. [Konferenz: Conference on Artificial Life, ALIFE 2022, online, July 18-22, 2022]
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 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) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 8 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 8 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 7 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 8 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 8 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
A customized niching methodology for the many-objective pathfinding problem
Weise, Jens; Mostaghim, Sanaz
In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI) / IEEE SSCI , 2021 - [Piscataway, NJ] : IEEE, insges. 8 S. [Symposium: IEEE Symposium Series on Computational Intelligence, SSCI, Online, 05. - 07. December 2021]
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. [Konferenz: 2021 IEEE Conference on Games, CoG, Copenhagen, Denmark, 17-20 August 2021]
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 [Tagung: 50. Jahrestagung der Gesellschaft für Informatik, virtual, 28. September bis 2. Oktober 2020]
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
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 , 2021 - Piscataway, NJ, USA : IEEE, S. 720-727 [Kongress: 2021 IEEE Congress on Evolutionary Computation, CEC, Kraków, Poland, 28 June-1 July 2021]
Tracking the heritage of genes in evolutionary algorithms
Benecke, Tobias; Mostaghim, Sanaz
In: 2021 IEEE Congress on Evolutionary Computation , 2021 - Piscataway, NJ, USA : IEEE, S. 1800-1807 [Kongress: 2021 IEEE Congress on Evolutionary Computation, CEC, Kraków, Poland, 28 June-1 July 2021]
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 , Francisco - New York,NY,United States : Association for Computing Machinery ; Chicano, Francisco . - 2021, S. 327-328 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '21, Lille, France, July 10 - 14, 2021]
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 , Jorge - New York,NY,United States : Association for Computing Machinery ; Lobo, Jorge . - 2021, S. 3-13 [Symposium: 26th ACM Symposium on Access Control Models and Technologies, virtual event Spain, June 16 - 18, 2021]
Many-objective pathfinding based on Fréchet similarity metric
Weise, Jens; Mostaghim, Sanaz
In: Evolutionary Multi-Criterion Optimization , 1st ed. 2021. - Cham : Springer International Publishing ; Ishibuchi, Hisao - 11th International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings, S. 375-386 - (Lecture notes in computer science; volume 12654) [Konferenz: 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021, Shenzhen, China, March 28-31, 2021]
Using neighborhood-based density measures for multimodal multi-objective optimization
Javadi, Mahrokh; Mostaghim, Sanaz
In: Evolutionary Multi-Criterion Optimization , 1st ed. 2021. - Cham : Springer International Publishing ; Ishibuchi, Hisao - 11th International Conference, EMO 2021, Shenzhen, China, March 28–31, 2021, Proceedings, S. 335-345 - (Lecture notes in computer science; volume 12654) [Konferenz: 11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021, Shenzhen, China, March 28-31, 2021]
Kooperation mittels Schwarmintelligenz
Mostaghim, Sanaz; Mai, Sebastian
In: Zusammenwirken von natürlicher und künstlicher Intelligenz - Wiesbaden : Springer VS ; Haux, Reinhold *1953-* . - 2021, S. 55-69
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)
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)
Dissecting neural networks filter responses for artistic style transfer
Uhde, Florian; Mostaghim, Sanaz
In: Artificial Intelligence in Music, Sound, Art and Design , 1st ed. 2021. - Cham : Springer International Publishing ; Romero, Juan, S. 297-312 - ( Lecture notes in computer science; volume 12693) [Konferenz: 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, Virtual Event, April 7-9, 2021]
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
A scalable many-objective pathfinding benchmark suite
Weise, Jens; Mostaghim, Sanaz
In: IEEE transactions on evolutionary computation / Institute of Electrical and Electronics Engineers - New York, NY : IEEE - a publication of the IEEE Neural Networks Council . - 2021 [Online first]
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 [Online first]
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. [Online first]
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), Heft 1, insges. 8 S.
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.
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 - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]
T-EA - a Traceable Evolutionary Algorithm
Ramirez-Atencia, Cristian; Benecke, Tobias; Mostaghim, Sanaz
In: 2020 IEEE Congress on Evolutionary Computation (CEC) , 2020 - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]
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 - Scitepress Digital Library ; Merelo, Juan Julian . - 2020, S. 155-166 [Konferenz: 12th International Joint Conference on Computational Intelligence, web-based event, 2-4 November 2020]
Modeling pathfinding for swarm robotics
Mai, Sebastian; Mostaghim, Sanaz
In: Swarm Intelligence - Cham : Springer Nature Switzerland AG ; Dorigo, Marco . - 2020, S. 190-202 - ( Lecture Notes in Computer Science; 12421) [Konferenz: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020]
A many-objective route planning benchmark problem for navigation
Weise, Jens; Mostaghim, Sanaz
In: GECCO'20 - New York, New York : The Association for Computing Machinery . - 2020, S. 183-184 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '20, Cancún Mexico, 8-12 July 2020]
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 - Piscataway, NJ, USA : IEEE, insges. 8 S. [Kongress: IEEE Congress on Evolutionary Computation, CEC, Glasgow, United Kingdom, 19-24 July 2020]
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 , 2020 - [Piscataway, NJ] : IEEE, S. 497 - 504 [Symposium: 2020 IEEE Symposium Series on Computational Intelligence, SSCI, Canberra, Australia, 1-4 December 2020]
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 [Symposium: 2020 IEEE Symposium Series on Computational Intelligence, SSCI, Canberra, Australia, 1-4 December 2020]
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 , 2020 - Piscataway, NJ : IEEE ; Webb, Geoff, S. 781-782 [Konferenz: 7th International Conference on Data Science and Advanced Analytics, DSAA, Sydney, Australia, 6-9 Oct. 2020]
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) , 2020 - [Piscataway, NJ] : IEEE, S. 487-493 [Konferenz: 17th International Conference on Ubiquitous Robots, UR, Kyoto, Japan, 22-26 June 2020]
Survey into predictive key performance indicator analysis from data mining perspective
Thakur, Akshay; Beck, Robert; Mostaghim, Sanaz; Grosmann, Daniel
In: 2020 IEEE 25th International Conference on Emerging Technologies and Factory Automation (ETFA) / IEEE International Conference on Emerging Technologies and Factory Automation , 2020 - Piscataway, NJ : IEEE ; IEEE International Conference on Emerging Technologies and Factory Automation (25.:2020), S. 476-483 [Konferenz: 25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, Vienna, Austria, 8-11 Sept. 2020]
Collective decision making in swarm robotics with distributed Bayesian Hypothesis Testing
Shan, Qihao; Mostaghim, Sanaz
In: Swarm Intelligence - Cham : Springer Nature Switzerland AG ; Dorigo, Marco . - 2020, S. 55-67 - ( Lecture Notes in Computer Science; 12421) [Konferenz: 12th International Conference, ANTS 2020, Barcelona, Spain, October 2628, 2020]
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
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
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 / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2020, insges. 10 S. [Online first]
Particle swarm contour search algorithm
Weikert, Dominik; Mai, Sebastian; Mostaghim, Sanaz
In: Entropy - Basel : MDPI - Volume 22(2020), issue 4, article 407, 15 Seiten
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, S. 1-6 [Konferenz: EUROGEN 2019, Guimarães, Portugal, September 12-14, 2019]
The effects of crowding distance and mutation in multimodal and multi-objective optimization problems
Javadi, Mahrokh; Zille, Heiner; Mostaghim, Sanaz
In: EUROGEN 2019 - Guimarães, S. 1-8 [Konferenz: EUROGEN 2019, Guimarães, Portugal, September 12-14, 2019]
Buchbeitrag
Performance of dynamic algorithms on the dynamic distance minimization problem
Heibig, Mardé; Zille, Heiner; Javadi, Mahrokh; Mostaghim, Sanaz
In: GECCO'19 - New York, New York : The Association for Computing Machinery ; López-Ibáñez, Manuel . - 2019, S. 205-206 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]
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, S. 407-408 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]
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 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]
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 , 2019 - Cham : Springer International Publishing ; Deb, Kalyanmoy, S. 399-410 - (Lecture notes in computer science; 11411) [Konferenz: 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019]
Modified crowding distance and mutation for multimodal multi-objective optimization
Javadi, Mahrokh; Zille, Heiner; Mostaghim, Sanaz
In: GECCO'19 - New York, New York : The Association for Computing Machinery ; López-Ibáñez, Manuel . - 2019, S. 211-212 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]
Ising model as a switch voting mechanism in collective perception
Bartashevich, Palina; Mostaghim, Sanaz
In: Progress in Artificial Intelligence - Cham : Springer ; Oliveira, Paulo Moura . - 2019, S. 617-629 - (Lecture Notes in Computer Science; vol.11805) [ EPIA 2019, Vila Real, Portugal, 03.-06.09.2019]
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) [EPIA 2019, Vila Real, Portugal, 03.-06.09.2019]
Benchmarking collective perception - new task difficulty metrics for collective decision-making
Bartashevich, Palina; Mostaghim, Sanaz
In: Progress in Artificial Intelligence - Cham : Springer ; Oliveira, Paulo Moura . - 2019, S. 699-711 - (Lecture Notes in Computer Science; vol.11805) [ EPIA 2019, Vila Real, Portugal, 03.-06.09.2019]
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, S. 1-8 [Konferenz: 2019 IEEE Conference on Games, CoG, London, United Kingdom, 20-23 August 2019]
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 [Konferenz: Genetic and Evolutionary Computation Conference Companion, GECCO '19, Prague, Czech Republic, July 13 - 17, 2019]
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), Heft 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) - (Lecture notes in computer science; 11411; Theoretical Computer Science and General Issues; 11411; Springer eBook Collection; SpringerLink; Bücher), ISBN: 978-3-030-12598-1 Kongress: Evolutionary Multi-Criterion Optimization Conference 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: Swarm intelligence / International Conference on Swarm Intelligence , 2018 - Cham : Springer, S. 431-432 - (Lecture Notes in Computer Science; 11172) [Konferenz: 11th International Conference on Swarm Intelligence, ANTS 2018, Rome, Italy, October 29-31, 2018]
Buchbeitrag
Vector field benchmark for collective search in unknown dynamic environments
Bartashevich, Palina; Knors, Welf; Mostaghim, Sanaz
In: Swarm intelligence / International Conference on Swarm Intelligence , 2018 - Cham : Springer ; Dorigo, Marco, S. 411-419 - (Lecture Notes in Computer Science; 11172) [Konferenz: 11th International Conference on Swarm Intelligence, ANTS 2018, Rome, Italy, October 29-31, 2018]
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 / Australasian Joint Conference on Artificial Intelligence , 2018 - 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]
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 [Konferenz: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018]
A survey on graph-based systems in manufacturing processes
Weise, Jens; Benkhardt, Steven; Mostaghim, Sanaz
In: 2018 SSCI proceedings / IEEE Symposium Series on Computational Intelligence , 2018 - Piscataway, NJ : IEEE, S. 112-119 [Konferenz: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018]
Understanding collective decision-making in natural swarms
Hasan, Asema; Mostaghim, Sanaz
In: 2018 SSCI proceedings / IEEE Symposium Series on Computational Intelligence , 2018 - Piscataway, NJ : IEEE, S. 1563-1570 [Konferenz: 2018 IEEE SSCI, Bangalore, India, 18 - 21 November, 2018]
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 [Konferenz: 2018 SSCI, Bangalore, India, 2018.11.18-21]
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) [Konferenz: 15th International Conference Parallel Problem Solving from Nature, PPSN XV, Coimbra, Portugal, September 8-12, 2018]
Evolving PSO algorithm design in vector fields using geometric semantic GP
Bartashevich, Paulina; Bakurov, Illya; Mostaghim, Sanaz; Vanneschi, Leonardo
In: GECCO'18 companion - New York, New York : The Association for Computing Machinery . - 2018, S. 262-263 [Konfernz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15 - 19, 2018]
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, S. 729-736 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15-19, 2018]
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 . - 2018, S. 77-84 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO '18, Kyoto, Japan, July 15-19, 2018]
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 , 2017 - Piscataway, NJ : IEEE ; 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]
Comparison study of large-scale optimisation techniques on the LSMOP benchmark functions
Zille, Heiner; Mostaghim, Sanaz
In: 2017 SSCI proceedings / IEEE Symposium Series on Computational Intelligence , 2017 - Piscataway, NJ : IEEE ; 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]
Towards a general framework for artistic style transfer
Uhde, Florian; Mostaghim, Sanaz
In: Computational Intelligence in Music, Sound, Art and Design - Cham : Springer . - 2018, S. 177-193 - (Lecture Notes in Computer Science; 10783) [Konferenz: 7th International Conference, EvoMUSART 2018, Parma, Italy, April 4-6, 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 , 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
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. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6th - 9th December, 2016, Athens, Greece; Copyright 2016]
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) , 2017 - Piscataway, NJ : IEEE ; IEEE Congress on Evolutionary Computation (2017), S. 1467-1473 [Kongress: 2017 IEEE Congress on Evolutionary Computation, CEC, Donostia-San Sebastián, Spain, 5-8 June, 2017]
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 - New York, NY : ACM . - 2017, S. 1216-1223 [Konferenz: Genetic and Evolutionary Computation Conference, GECCO 2017, Berlin, Germany, 15 - 19 July, 2017]
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) , 2017 - [Piscataway, NJ] : IEEE ; Computer Science and Electronic Engineering Conference (9.:2017), S. 189-194 [Konferenz: 9th Computer Science and Electronic Engineering Conference (CEEC), Essex, UK, 27th-29th September 2017]
Influence of dynamic environments on agent strategies
Piper, Franz; Mostaghim, Sanaz
In: 2016 IEEE Symposium Series on Computational Intelligence (SSCI) , 2016 - Piscataway, NJ : IEEE . - 2017, insges. 8 S. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6th - 9th December, 2016, Athens, Greece; Copyright 2016]
Dynamic distance minimization problems for dynamic multi-objective optimization
Zille, Heiner; Kottenhahn, André; Mostaghim, Sanaz
In: 2017 IEEE Congress on Evolutionary Computation (CEC) , 2017 - Piscataway, NJ : IEEE ; IEEE Congress on Evolutionary Computation (2017), S. 952-959 [Kongress: 2017 IEEE Congress on Evolutionary Computation, CEC, Donostia-San Sebastián, Spain, 5-8 June, 2017]
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) , 2017 - Piscataway, NJ : IEEE ; IEEE Congress on Evolutionary Computation (2017), S. 1263-1270 [Kongress: 2017 IEEE Congress on Evolutionary Computation, CEC, Donostia-San Sebastián, Spain, 5-8 June, 2017]
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) , 2016 - Piscataway, NJ : IEEE . - 2017, insges. 8 S. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 6th - 9th December, 2016, Athens, Greece; Copyright 2016]
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 - [Setúbal] : SCITEPRESS - Science and Technology Publications, Lda. . - 2017, S. 35-44 [Konferenz: 9th International Joint Conference on Computational Intelligence, IJCCI 2017, Funchal, Madeira, Portugal, November 1-3, 2017]
Comparison study of large-scale optimisation techniques on the LSMOP benchmark functions
Zille, Heiner; Mostaghim, Sanaz
In: 2017 SSCI proceedings - Piscataway, NJ : IEEE, S. 2817-2824
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, S. 1848-1855
Begutachteter Zeitschriftenartikel
Heterogeneous evolutionary swarms with partial redundancy solving multi-objective tasks
Moritz, Ruby L. V.; Mostaghim, Sanaz
In: Evolutionary multi-criterion optimization / EMO , 2017 - 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]
Solving the Bi-objective Traveling Thief Problem with multi-objective evolutionary algorithms
Blank, Julian; Deb, Kalyanmoy; Mostaghim, Sanaz
In: Evolutionary multi-criterion optimization / EMO , 2017 - 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]
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), Heft 1/2, S. 71-81
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 / Institute of Electrical and Electronics Engineers - New York, NY : IEEE . - 2017, insges. 16 S.
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)
Frontiers in Computational Intelligence
Mostaghim, Sanaz; Nürnberger, Andreas; Borgelt, Christian
In: [s.l.]: Springer International Publishing AG 2018, Online-Ressource (IX, 143 p. 43 illus., 32 illus. in color, online resource) - (Studies in Computational Intelligence; 739; SpringerLink; Bücher), ISBN: 978-3-319-67789-7
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. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 6-9 December, 2016]
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 - Piscataway, NJ : IEEE, insges. 8 S. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 6-9 December, 2016]
Influence of dynamic environments on agent strategies
Pieper, Franz; Mostaghim, Sanaz
In: The 2016 IEEE Symposium Series on Computational Intelligence - Piscataway, NJ : IEEE, insges. 8 S. [Kongress: 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 6-9 December, 2016]
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, S. 3316-3323 [Kongress: IEEE World Congress on Computational Intelligence, IEEE WCCI 2016, Vancouver, Canada, 24 - 29 July, 2016]
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]
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 ; Friedrich, Tobias, S. 83-84 [Kongress: 2016 on Genetic and Evolutionary Computation Conference Companion, GECCO '16, Denver, 20. - 24. July, 2016]
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]
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, 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 : [Verlag nicht ermittelbar] - 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, Dissertation Otto-von-Guericke-Universität Magdeburg, Fakultät für Informatik 2016, xii, 151 Seiten [Literaturverzeichnis: Seite 139-150][Literaturverzeichnis: Seite 139-150]
Artikel in Kongressband
Mixed-reality simulation environment for a swarm of autonomous indoor quadcopters
Steup, Christoph; Mostaghim, Sanaz; Mäurer, Lukas; Velinov, Vladimir
In: Rotorcraft Virtual Engineering Conference , 2016 - [London] - 2016, paper 5.17, insgesamt 11 S. [Kongress: Rotorcraft Virtual Engineering Conference, Liverpool, 8-10 November, 2016]
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
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
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 - Piscataway, NJ : IEEE, S. 845-852
Properties of scalable distance minimization problems using the Manhattan metric
Zille, Heiner; Mostaghim, Sanaz
In: 2015 IEEE Congress on Evolutionary Computation (CEC 2015) - Piscataway, NJ : IEEE, S. 2875-2882 [Kongress: IEEE Congress on Evolutionary Computation (CEC 2015), Sendai, 25-28 May 2015]
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 - IEEE, insges. 8 S. [Workshop on Self-Optimisation in Organic and Autonomic Computing Systems (SAOS15)]
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
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) - Piscataway, NJ : IEEE . - 2015, insges. 1 S. [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; Copyright 2014]
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) - Piscataway, NJ : IEEE . - 2015, insges. 2 S. [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; Copyright 2014]
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) - Piscataway, NJ : IEEE, S. 207-212 Kongress: CEEC 7 Colchester 2015.09.24-25
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 / Institute of Electrical and Electronics Engineers - New York, NY : IEEE, Bd. 7 (2015), Heft 4, S. 347 - 360
Multiobjective Optimization for Interwoven Systems
Ishibuchi, Hisao; Klamroth, Kathrin; Mostaghim, Sanaz; Naujoks, Boris; Poles, Silvia; Purshouse, Robin; Rudolph, Günter; Ruzika, Stefan
In: Dagstuhl Reports / Schloss Dagstuhl, Leibniz-Zentrum für Informatik - Wadern : Schloss Dagstuhl, Bd. 5 (2015), Heft 1, S. 139-150 [Dagstuhl Seminar 15031]
Confidence measure - a novel metric for robust meta-heuristic optimisation algorithms
Mirjalili, Seyedali; Lewis, Andrew; Mostaghim, Sanaz
In: Information sciences - 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)
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
Self-organized swarm display
Merkel, Sabrina; Mostaghim, Sanaz; Schmeck, Hartmut
In: International Journal of Swarm Intelligence: IJSI - Genève: Inderscience Enterprises, 2014
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
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
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
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
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
Multi-iterated Swarm
Britto, Andre; Mostaghim, Sanaz; Pozo, Ana
In: Genetic and Evolutionary Computation Conference (GECCO), pages 56 – 64, July 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
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
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
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
2011
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
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
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
2010
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
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
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
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
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
Studies in Computational Intelligence: Preface
Lewis, A.; Mostaghim, S.; Randall, M.
In: Studies in Computational Intelligence, Vol. 210, 2009, S. V-IX, ISSN 1860949X
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
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
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
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
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
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
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
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- Computational Intelligence
- Multikriterielle Optimierungalgorithmen
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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 | Universitätsprofessorin, Lehrstuhl für Computational Intelligence, Institut 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 |
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.
- Bachelor-Master-Kolloquium CI ( Link zur LV im LSF )
- Bachelor-Master-Theses-Supervision CI ( Link zur LV im LSF )
- Individual Projekt: SwarmLab ( Link zur LV im LSF )
- Intelligente Systeme ( Link zur LV im LSF )
- Intelligente Systeme ( Link zur LV im LSF )
- Seminar: Advanced Topics in Computational Intelligence and Bioinformatics ( Link zur LV im LSF )
- Seminar: Foundations of Computational Intelligence ( Link zur LV im LSF )
- Swarm Intelligence ( Link zur LV im LSF )
- Swarm Intelligence ( Link zur LV im LSF )
- Team Project: SwarmLab ( Link zur LV im LSF )