IMODE: Improving Multi-Objective Differential Evolution Algorithm

Authors:
JiShan Fan;ShengWu Xiong;JingZhuo Wang;ChengLong Gong
Affiliations:
-;-;-;-
Venue:
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 01
Year:
2008

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Multi-objective evolutionary algorithms based on the summation of normalized objectives and diversified selection

Information Sciences: an International Journal

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Abstract

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, andεdominance. The solutions provided by the IMODE algorithm for five standard test problems, is competitive to three known multi-objective optimization algorithms.