Effective multi-objective evolutionary algorithm

This paper proposes a novel multi-objective evolutionary algorithm based on a novel crossover operation and improves 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.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.