IMODE: Improving Multi-Objective Differential Evolution Algorithm
JiShan Fan, ShengWu Xiong, Jingzhuo Wang, ChengLong Gong · 2008
Differential Evolutionary (DE) is an evolutionary algorithm that was developed to handle optimization problems. DE is a simple algorithm, but it has been successfully applied to selected real world multi-objective problems. In this paper, Improving Multi-objective Differential Evolutionary (IMODE) is a new approach to solve multi-objective optimization based on basic DE. This algorithm is equipped with contour line to select candidate individuals, and combines with the crowding distance sorting and Pareto-based ranking, and epsiv dominance. The solutions provided by the IMODE algorithm for five standard test problems, is competitive to three known multi-objective optimization algorithms.