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

Hsien-Chung Wu

International Journal of Systems Science, 2022, vol. 53, issue 14, 3095-3111

Abstract: A new methodology is proposed in this paper to solve multiobjective optimisation problems (MOPs) by invoking genetic algorithms and solutions concepts of cooperative games. The weighting problems that are formulated by assigning some suitable weights to the multiple objective functions are usually solved to obtain the Pareto optimal solutions of MOPs. In this paper, the suitable weights will be taken from the core values of a cooperative game that is formulated from the original MOP by regarding the objective functions as players. Under these settings, we shall obtain a large set of all so-called Core-Pareto optimal solutions. In order to choose the best Core-Pareto optimal solution from this set, we shall invoke the genetic algorithms by setting a reasonable fitness function.

Date: 2022
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DOI: 10.1080/00207721.2022.2070793

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