一种采用聚类单纯形搜索的引力算法

doi:10.3969/j.issn.1001-2400.2014.06.017

Abstract

Abstract:

An improved central force optimization (CFO) is proposed based on the clustering and simplex method for global optimization. The clustering simplex (CS) operator is introduced to a new algorithm in the evolution process. Vertices of simplex are selected by clustering methods, and a periodical migrating of the best individual is introduced by the CS operator. CS can get away from local converged points by virtue of CFO, and CFO can improve its local exploiting capability and effectively speed up the convergence under the help of CS. Experimental results show that the proposed hybrid CSCFO algorithm is better than other algorithms in convergent speed and searching precision.

Key words: central force optimization, cluster analysis, simplex, global optimization

CLC Number:

TP301

LIU Jie;WANG Yuping. Central force optimization algorithm via clustering simplex search[J].J4, 2014, 41(6): 100-105.

References

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Central force optimization algorithm via clustering simplex search

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