Improved NSGA-II Algorithm for Optimization of Constrained Functions

摘要

In order to solve the constrained multi-objective optimization problem, an improved NSGA-II algorithm is proposed. On the basis of NSGA, the cross operation of the feasible and unfeasible solution is implemented in order to give full play to the role of the infeasible solution in the optimization process. In addition, the external preservation set is updated on the basis of the obtained dominant individual to preserve the optimal solution of the problem. The improved algorithm is applied to typical test functions and compared with NSGA-II. The experimental results show that the algorithm is superior.