A Survey on Cooperative Co-Evolutionary Algorithms
| Autor: | Zexuan Zhu, Ke Tang, Zhengping Liang, Xiaodong Li, Xiaoliang Ma, Qingfu Zhang, Weixin Xie |
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| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
Optimization problem Computer science Evolutionary algorithm 02 engineering and technology Theoretical Computer Science Computational Theory and Mathematics Genetic algorithm 0202 electrical engineering electronic engineering information engineering Benchmark (computing) Decomposition (computer science) Resource allocation 020201 artificial intelligence & image processing Resource management Software Selection (genetic algorithm) |
| Zdroj: | IEEE Transactions on Evolutionary Computation. 23:421-441 |
| ISSN: | 1941-0026 1089-778X |
| DOI: | 10.1109/tevc.2018.2868770 |
| Popis: | The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong in 1994 and since then many CCEAs have been proposed and successfully applied to solving various complex optimization problems. In applying CCEAs, the complex optimization problem is decomposed into multiple subproblems, and each subproblem is solved with a separate subpopulation, evolved by an individual evolutionary algorithm (EA). Through cooperative co-evolution of multiple EA subpopulations, a complete problem solution is acquired by assembling the representative members from each subpopulation. The underlying divide-and-conquer and collaboration mechanisms enable CCEAs to tackle complex optimization problems efficiently, and hence CCEAs have been attracting wide attention in the EA community. This paper presents a comprehensive survey of these CCEAs, covering problem decomposition, collaborator selection, individual fitness evaluation, subproblem resource allocation, implementations, benchmark test problems, control parameters, theoretical analyses, and applications. The unsolved challenges and potential directions for their solutions are discussed. |
| Databáze: | OpenAIRE |
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