A fast multi-objective differential evolutionary algorithm based on sorting of non-dominated solutions

Abstract

The multi-objective differential evolution based on Pareto domination is researched. It is found that there are some redundant operations in classic multi-objective evolutionary. Based on the non-dominated solution sorted and its potential features, we introduce a sorting method which only handles the highest rank individuals in current population. During the sorting operation, individuals can be chosen into the next generation. When the next generation is fully the algorithm is broken. Our method reduces the number of individuals for sorting process and the time complexity. In addition, a method of uniform crowding distance calculation is given. Finally, we incorporate the introduced sorting method and uniform crowding distance into differential evolution to propose a fast multi-objective differential evolution algorithm. Simulation results show that the proposed algorithm has greatly improved in terms of time complexity and performance.