A new approach based on Gaussian degree of closeness for solving multi-objective optimization problems

The Pareto set of optimal solutions resulting from solving multi-objective optimization problems, although on the one hand increases the flexibility in choosing an optimal solution according to the conditions of a system, but on the other hand, due to different tastes and perspectives in a The system, choosing the most desirable Pareto front answer, can be a serious challenge. In this regard, in this article, in the first step, by defining the concept of Gaussian degree of proximity and presenting a decomposition approach based on it, we produce the Pareto front, which numerical results show that this front in comparison with fronts obtained from other quality decomposition approaches. Has a higher. In the second step, due to the lack of an evaluation criterion that examines the quality of a front from different angles, we present a new evaluation criterion for comparing different fronts, which by considering both factors of mastery and proximity to the optimal answer. Examines the quality of the answers on a Pareto front. The results obtained from the simulation of the proposed steps on the existing standard test functions confirm the efficiency and effectiveness of each of the steps of the proposed problem.