Using Shapley Values and Genetic Algorithms to Solve Multiobjective Optimization Problems

This paper proposes a new methodology to solve multiobjective optimization problems by invoking genetic algorithms and the concept of Shapley values cooperative games. It is well known that Pareto-optimal solutions can be obtained solving corresponding weighting are formulated assigning some suitable weights objective functions. In this paper, we game from original problem regarding functions as players. The payoff function involves symmetric concept, which means only depends on number players in coalition independent role coalition. case, reasonably set up game. Under these settings, obtain so-called Shapley–Pareto-optimal solution. order choose best solution, used setting reasonable fitness function.