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2009
IEEE

An adaptive coevolutionary Differential Evolution algorithm for large-scale optimization

9 years 5 months ago
An adaptive coevolutionary Differential Evolution algorithm for large-scale optimization
— In this paper, we propose a new algorithm, named JACC-G, for large scale optimization problems. The motivation is to improve our previous work on grouping and adaptive weighting based cooperative coevolution algorithm, DECC-G [1], which uses random grouping strategy to divide the objective vector into subcomponents, and solve each of them in a cyclical fashion. The adaptive weighting mechanism is used to adjust all the subcomponents together at the end of each cycle. In the new JACC-G algorithm: (1) A most recent and efficient Differential Evolution (DE) variant, JADE [2], is employed as the subcomponent optimizer to seek for a better performance; (2) The adaptive weighting is time-consuming and expected to work only in the first few cycles, so a detection module is added to prevent applying it arbitrarily; (3) JADE is also used to optimize the weight vector in adaptive weighting process instead of using a basic DE in previous DECC-G. The efficacy of the proposed JACC-G algorith...
Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao, Art
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where CEC
Authors Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao, Arthur C. Sanderson
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