1. Improved multi-objective hybrid differential evolution algorithm.
- Author
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WANG Xiao-zhen and YU Guo-yan
- Subjects
- *
DIFFERENTIAL evolution , *ALGORITHMS , *MULTIDISCIPLINARY design optimization , *PROBLEM solving , *COMPUTER simulation , *STOCHASTIC convergence - 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]
- Published
- 2014
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