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Improved parallel chaos optimization algorithm
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AI
DOI：10.1016/j.amc.2012.09.053.png)
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Abstract
En 中文
Chaos optimization algorithm (COA), which has the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The design of approaches to improve the convergence of the COA is a challenging issue. Improved mutative-scale parallel chaotic optimization algorithm (MPCOA) are proposed in this paper, and three ways of improvements for MPCOA are investigated in detail: MPCOA combined with simplex search method, MPCOA based on competitive/cooperative inter-communication, MPCOA combined with harmony search algorithm. Several simulation results are used to show the effective performance of these chaos optimization algorithms. (C) 2012 Elsevier Inc. All rights reserved.
Keywords:
Hybrid optimization algorithm
Chaos optimization algorithm (COA)
Harmony search algorithm
Simplex search method
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IF:
3.4
Papers:
2.3W
Citations:
3.3W
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