基于精英选择和个体迁移的多约束多目标问题求解

new evolutionary algorithm for multi-constraint handing problem is proposed to improve the existed limitation. In this paper, constrained fitness function is applied to quantify the extent of the constraint violation, which takes both the number of violated constraints and the amount of constraint violation into account in order to measure the quality of individual solutions in more accurate way. Definitions of Pareto domination and Pareto optimal solutions are renewed according to the constrained fitness function. And evolutionary algorithm based on elitist selection and individual migration is applied to solving the multi-objective and multi-constrained problems. Experiments on test functions manifest that the proposed method can converge to Pareto frontier solutions, and the spread of solutions is uniformly. The proposed method has superiority over the multi-objective and multi-constrained problems.