An Adaptive Multiobjective Differential Evolution Algorithm
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| Title | An Adaptive Multiobjective Differential Evolution Algorithm |
| Authors | |
| Abstract | The mutation strategy and control parameter have a significant influence on the performance of differential evolution. An local and global mutation operator based subregion and external set strategies are proposed in this paper. They use the idea of direct simplexmethod of mathematical programming. It is advantageous to search the better solutions in the search space. The local mutation operator is applied to improve the local search performance of the algorithm and accelerate convergence speed. The global mutation operator is usedto exploit a wider area and jump out of the local optima. Anadaptive strategy for assigning mutation strategies and control parameters is proposed in this paper. The more successful is a mutation strategy and control parameter setting in the previous search, the more chance it will be used in the further search. Moreover, a novel crossover operator based subregion and external set strategy also is introduced. In order to demonstrate the performance of the proposed algorithm, it is compared with the MOEA/D-DE and the hybrid-NSGA-II-DE. The result indicates that the proposed algorithm is efficient. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2013-02-01 |
| Source | Journal of Computers Vol 8, No 2 (2013): Special Issue: Advances in Computational Intelligence |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |