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On the selection of solutions for mutation in differential evolution
- Source :
- Frontiers of Computer Science. 12:297-315
- Publication Year :
- 2018
- Publisher :
- Springer Science and Business Media LLC, 2018.
-
Abstract
- Differential evolution (DE) is a kind of evolutionary algorithms, which is suitable for solving complex optimization problems. Mutation is a crucial step in DE that generates new solutions from old ones. It was argued and has been commonly adopted in DE that the solutions selected for mutation should have mutually different indices. This restrained condition, however, has not been verified either theoretically or empirically yet. In this paper, we empirically investigate the selection of solutions for mutation in DE. From the observation of the extensive experiments, we suggest that the restrained condition could be relaxed for some classical DE versions as well as some advanced DE variants. Moreover, relaxing the restrained condition may also be useful in designing better future DE algorithms.
- Subjects :
- Mathematical optimization
021103 operations research
Optimization problem
General Computer Science
Computer science
0211 other engineering and technologies
Evolutionary algorithm
02 engineering and technology
Theoretical Computer Science
Differential evolution
Mutation (genetic algorithm)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Selection (genetic algorithm)
Subjects
Details
- ISSN :
- 20952236 and 20952228
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Frontiers of Computer Science
- Accession number :
- edsair.doi...........1c52b20d33df4c31a60381919e7e7dd9
- Full Text :
- https://doi.org/10.1007/s11704-016-5353-5