NSGA-II genetic algorithm-based laminated welding spot stress and return loss dual-objective optimization method and storage medium

The invention discloses a laminated welding spot stress and return loss dual-objective optimization system operation method based on an NSGA-II genetic algorithm. The method comprises the following steps: establishing a dual-objective optimization mathematical model of a laminated welding spot based on a response surface method; optimizing the structure parameters of the laminated welding spots on the dual-objective optimization mathematical model by using an NSGA-II algorithm to obtain a Pareto optimal solution set of the structure parameters of the laminated welding spots and stress and return loss; using entropy weight TOPSIS decision analysis to find out a group of optimal laminated welding spot structure parameter horizontal combinations from the Pareto optimization solution set to achieve the purpose of laminated welding spot structure parameter dual-objective optimization; according to the method, scientificity and feasibility of structural parameters of the laminated welding spots are promoted, and th