A modified algorithm for multi-objective constrained optimization problems

A modified algorithm is proposed according to the multi-objective constrained optimization problems. In order to let constraint conditions convert to an optimization objective used a transform strategy, which is a satisfactory summation function of constraint conditions, to accelerate the convergence rate, a new region changed acceleration mechanism is used, and for shake of improving the local search ability, chaos search technology is introduced. This modified algorithm not only improves the diversity of solution set but also makes the nondominated solutions approach the Pareto set as close as possible. At last, the algorithm is applied to three classical test functions; the optimization performance of modified algorithm is evaluated and numerical experimental results show the effectiveness of the proposed method.