Paper Info
Title
A Survey on Cooperative Co-evolutionary Algorithms
Abstract
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.
Year
DOI
Venue
2019
10.1109/tevc.2018.2868770
IEEE Transactions on Evolutionary Computation
Keywords
Field
DocType
Optimization,Genetic algorithms,Resource management,Benchmark testing,Computer science,Google,Perturbation methods
Resource management,Mathematical optimization,Evolutionary algorithm,Implementation,Resource allocation,Optimization problem,Genetic algorithm,Mathematics,Benchmark (computing)
Journal
Volume
Issue
ISSN
23
3
1089-778X
Citations 
PageRank 
References 
10
0.44
0
Authors
7
Name
Order
Citations
PageRank
Xiaoliang Ma118218.51
Xiaodong Li242840.14
Qingfu Zhang37634255.05
Tang Ke42798139.09
Zhengping Liang51068.81
Weixin Xie665162.35
Zexuan Zhu798957.41