Research Article 
Dual-system Cooperative Coevolutionary Differential Evolution Algorithm for Solving Nonseparable Function Optimization
Feng-Zhe Cui, Lei Wang, Zhi-Zheng Xu, Xiu-Kun Wang and Hong-Fei Teng
Information Technology Journal, 2013, 12(9), 1796-1803.
Abstract
In recent years, researches on high-dimensional nonseparable function optimization have made progress. Approaches based on Potter’s Cooperative Coevolutionary (CC) framework have achieved better results and aroused a great attention. However, the computational results are still unsatisfying for most Benchmark functions. Therefore, this study develops a dual-system (population) cooperative coevolutionary differential evolution (DCCDE) algorithm based on dual-system Evolutionary Algorithm (EA). This algorithm adopts a variable static grouping pattern and a improved Differential Evolution (DE) algorithm combined with simple crossover (SPX) local search strategy and modifies the migration pattern of the sub-individuals (not subpopulations) among the subsystems (subgroups of variables) in the dual-system. The test results of 20 Benchmark functions (including 17 nonseparable functions, dimension D = 1000) show that the proposed algorithm is better than other algorithms in computational accuracy.
ASCI-ID: 28-2053
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