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Improved multi-objective hybrid differential evolution algorithm.

Authors :
WANG Xiao-zhen
YU Guo-yan
Source :
Application Research of Computers / Jisuanji Yingyong Yanjiu. May2014, Vol. 31 Issue 5, p1332-1335. 4p.
Publication Year :
2014

Abstract

By using the differential evolution algorithm (DE) to solve multi-objective optimization problems, this paper proposed a Pareto optimal solution migration based differential evolution for multi-objective optimization (PSDEMO) to guarantee the diversity of Pareto optimal solution. It adopted the elitist strategy in the algorithm, and archived Pareto non-dominance solutions found in the evolution operation dynamically with the evolution process. In addition, it used all the non-dominance solutions in the archive to do migration operation after mutation and crossover operation of DE to increase the number and quality of non-dominated solutions. Compared with standard DE, simulation results show that the PSDEMO not only helps to improve the quantity of the Pareto non-dominance solution, but also has good balance keeping ability between the diversity and convergence. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10013695
Volume :
31
Issue :
5
Database :
Academic Search Index
Journal :
Application Research of Computers / Jisuanji Yingyong Yanjiu
Publication Type :
Academic Journal
Accession number :
95780836
Full Text :
https://doi.org/10.3969/j.issn.1001-3695.2014.05.011