Solving multiobjective optimisation problems using genetic algorithms and solutions concepts of cooperative games

DOI10.1080/00207721.2022.2070793zbMath1506.90242OpenAlexW4280541577MaRDI QIDQ5046877

Hsien-Chung Wu

Publication date: 9 November 2022

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2022.2070793

zbMATH Keywords

game theorygenetic algorithmsPareto optimal solutionsmultiobjective optimisationweighting problemscore values

Mathematics Subject Classification ID

Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Multi-objective and goal programming (90C29) Cooperative games (91A12) Applications of game theory (91A80)

Cites Work

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• Theory of multiobjective optimization
• Monotonic solutions of cooperative games
• Group decision making under multiple criteria. Methods and applications
• Multiple-criteria decision making. Concepts, techniques, and extensions. With the assistance of Yoon-Ro Lee and Antonie Stam
• Multiple attribute decision making. Methods and applications. A state-of- the-art survey
• Multiobjective programming and planning
• Linear multiobjective programming
• Multiple objective decision making - methods and applications. A state- of-the-art survey. In collaboration with Sudhakar R. Paidy and Kwangsun Yoon
• Scatter search. Methodology and implementation in C. With CD-ROM.
• Multiobjective evolutionary algorithms and applications.
• Models in Cooperative Game Theory
• Game Theory
• Two-Person Cooperative Games
• Evolutionary algorithms for single and multicriteria design optimization
• Genetic algorithms and fuzzy multiobjective optimization