关键词: 多目标优化问题, 多目标演化算法, Pareto最优

Abstract: This paper proposes a novel muiti-objective evolutionary algorithm, based on a novel crossover operation and improved crowding operation of NSGA-II ,in order to quicken further rate of convergence of solutions to Pareto optimal front and improve precision of solutions. The numeric experiments results indicate the new algorithm is very efficient for multi-objective test problems of high-dimension with Pareto optimal front of convex or non-convex or discontinuous and convex and multi-modal. The obtained non-dominated solutions have a good distribution property. But as to high-dimension functions with too many local Pareto optimal fronts, it traps in local Pareto optimal front easily.

Key words: multi-objective optimization problem, muiti-objective evolutionary algorithm, Pareto optimality