Dagstuhl Seminar 23361
Multiobjective Optimization on a Budget
( Sep 03 – Sep 08, 2023 )
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Organizers
- Richard Allmendinger (University of Manchester, GB)
- Carlos M. Fonseca (University of Coimbra, PT)
- Serpil Sayin (Koc University - Istanbul, TR)
- Margaret M. Wiecek (Clemson University, US)
Contact
- Marsha Kleinbauer (for scientific matters)
- Jutka Gasiorowski (for administrative matters)
Dagstuhl Reports
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Multiobjective optimization (MO), a discipline within systems science that provides models, theories, and methodologies to address decision-making problems under conflicting objectives, has a myriad of applications in all areas of human activity, ranging from business and management to engineering. The proposed seminar is motivated by the desire to continue to make MO useful to society as it faces complex decision-making problems and experiences limited resources for decision making. Of particular interest are processes that evolve competitively in environments with scarce resources and lead to decision problems that are characterized by multiple, incommensurate, and conflicting objectives, and engage multiple decision-makers.
The Dagstuhl Seminar will focus on three major types of resource limitations: methodological (e.g., number of solution evaluations), technical (e.g., computation time, energy consumption), and human-related (e.g., decision maker availability and responsiveness). The effect of these limitations on optimization and decision-making quality, as well as methods to quantify and mitigate this influence, will be of particular interest. These methods include reduction and decomposition of optimization and decision-making models; representation of solution sets; different types of optimization approaches such as coordination-based, Bayesian, and multi-stage; preference acquisition; and benchmarking of algorithms. Applications within engineering-design optimization, simulation optimization, and experiment-based optimization will serve as motivation.
Following on the tradition of earlier Dagstuhl Seminars on multiobjective optimization, the seminar will be a platform for experts in two main research communities - Evolutionary MO (EMO) and Multiobjective Decision Making (MCDM) - to propose and discuss novel ideas related to modeling, theory, and applications of MO under competitive conditions and limited budgets.
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Richard Allmendinger, Carlos M. Fonseca, Serpil Sayin, and Margaret M. Wiecek
- Thomas Bäck (Leiden University, NL) [dblp]
- Mickaël Binois (INRIA - Sophia Antipolis, FR) [dblp]
- Fritz Bökler (Universität Osnabrück, DE) [dblp]
- Jürgen Branke (University of Warwick, GB) [dblp]
- Dimo Brockhoff (INRIA Saclay - Palaiseau, FR) [dblp]
- Tinkle Chugh (University of Exeter, GB) [dblp]
- Kerstin Dächert (HTW Dresden, DE) [dblp]
- Benjamin Doerr (Ecole Polytechnique - Palaiseau, FR) [dblp]
- Matthias Ehrgott (Lancaster University, GB) [dblp]
- Gabriele Eichfelder (TU Ilmenau, DE) [dblp]
- Jonathan Fieldsend (University of Exeter, GB) [dblp]
- Carlos M. Fonseca (University of Coimbra, PT) [dblp]
- Susan R. Hunter (Purdue University, US) [dblp]
- Ekhine Irurozki (Telecom Paris, FR) [dblp]
- Hisao Ishibuchi (Southern Univ. of Science and Technology - Shenzen, CN) [dblp]
- Andrzej Jaszkiewicz (Poznan University of Technology, PL) [dblp]
- Pascal Kerschke (TU Dresden, DE) [dblp]
- Kathrin Klamroth (Universität Wuppertal, DE) [dblp]
- Joshua D. Knowles (Schlumberger Cambridge Research, GB) [dblp]
- Karl Heinz Küfer (Fraunhofer ITWM - Kaiserslautern, DE) [dblp]
- Arnaud Liefooghe (University of Lille, FR) [dblp]
- Kaisa Miettinen (University of Jyväskylä, FI) [dblp]
- Juliane Mueller (NREL - Golden, US) [dblp]
- Boris Naujoks (TH Köln, DE) [dblp]
- Aneta Neumann (University of Adelaide, AU) [dblp]
- Frank Neumann (University of Adelaide, AU) [dblp]
- Markus Olhofer (HONDA Research Institute Europe GmbH - Offenbach, DE) [dblp]
- Luís Paquete (University of Coimbra, PT) [dblp]
- Robin Purshouse (University of Sheffield, GB) [dblp]
- Alma Rahat (Swansea University, GB) [dblp]
- Andrea Raith (University of Auckland, NZ) [dblp]
- Enrico Rigoni (ESTECO SpA - Trieste, IT) [dblp]
- Stefan Ruzika (RPTU - Kaiserslautern, DE) [dblp]
- Serpil Sayin (Koc University - Istanbul, TR) [dblp]
- Anita Schöbel (Fraunhofer ITWM - Kaiserslautern, DE) [dblp]
- Britta Schulze (Universität Wuppertal, DE) [dblp]
- Ralph E. Steuer (University of Georgia, US) [dblp]
- Michael Stiglmayr (Universität Wuppertal, DE) [dblp]
- Tea Tusar (Jozef Stefan Institute - Ljubljana, SI) [dblp]
- Daniel Vanderpooten (University Paris-Dauphine, FR) [dblp]
- Vanessa Volz (modl.ai - Copenhagen, DK) [dblp]
- Hao Wang (Leiden University, NL) [dblp]
- Margaret M. Wiecek (Clemson University, US) [dblp]
- Kaifeng Yang (Univ. of Applied Sciences - Hagenberg, AT)
Related Seminars
- Dagstuhl Seminar 04461: Practical Approaches to Multi-Objective Optimization (2004-11-07 - 2004-11-12) (Details)
- Dagstuhl Seminar 06501: Practical Approaches to Multi-Objective Optimization (2006-12-10 - 2006-12-15) (Details)
- Dagstuhl Seminar 09041: Hybrid and Robust Approaches to Multiobjective Optimization (2009-01-18 - 2009-01-23) (Details)
- Dagstuhl Seminar 12041: Learning in Multiobjective Optimization (2012-01-22 - 2012-01-27) (Details)
- Dagstuhl Seminar 15031: Understanding Complexity in Multiobjective Optimization (2015-01-11 - 2015-01-16) (Details)
- Dagstuhl Seminar 18031: Personalized Multiobjective Optimization: An Analytics Perspective (2018-01-14 - 2018-01-19) (Details)
- Dagstuhl Seminar 20031: Scalability in Multiobjective Optimization (2020-01-12 - 2020-01-17) (Details)
Classification
- Machine Learning
- Neural and Evolutionary Computing
- Systems and Control
Keywords
- decision making
- expensive optimization
- few-shot learning
- evolutionary algorithms
- simulation optimization
