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论文类型：期刊论文

发表时间：2012-01-01

发表刊物：JOURNAL OF GLOBAL OPTIMIZATION

收录刊物：Scopus、SCIE、EI

卷号：52

期号：1

页面范围：45-55

ISSN号：0925-5001

关键字：Global optimization; Heuristic; Real-coded; Evolutionary algorithm; Differential evolution; Low dimensional simplex evolution

摘要：This paper presents a new heuristic for global optimization named low dimensional simplex evolution (LDSE). It is a hybrid evolutionary algorithm. It generates new individuals following the Nelder-Mead algorithm and the individuals survive by the rule of natural selection. However, the simplices therein are real-time constructed and low dimensional. The simplex operators are applied selectively and conditionally. Every individual is updated in a framework of try-try-test. The proposed algorithm is very easy to use. Its efficiency has been studied with an extensive testbed of 50 test problems from the reference (J Glob Optim 31:635-672, 2005). Numerical results show that LDSE outperforms an improved version of differential evolution (DE) considerably with respect to the convergence speed and reliability.