文章基本信息

标题：Hybridization of Adaptive Differential Evolution with an Expensive Local Search Method
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作者：Rashida Adeeb Khanum ; Muhammad Asif Jan ; Nasser Mansoor Tairan 等
期刊名称：Journal of Optimization
电子版ISSN：2314-6486
出版年度：2016
卷号：2016
DOI：10.1155/2016/3260940
出版社：Hindawi Publishing Corporation
摘要：Differential evolution (DE) is an effective and efficient heuristic for global optimization problems. However, it faces difficulty in exploiting the local region around the approximate solution. To handle this issue, local search (LS) techniques could be hybridized with DE to improve its local search capability. In this work, we hybridize an updated version of DE, adaptive differential evolution with optional external archive (JADE) with an expensive LS method, Broydon-Fletcher-Goldfarb-Shano (BFGS) for solving continuous unconstrained global optimization problems. The new hybrid algorithm is denoted by DEELS. To validate the performance of DEELS, we carried out extensive experiments on well known test problems suits, CEC2005 and CEC2010. The experimental results, in terms of function error values, success rate, and some other statistics, are compared with some of the state-of-the-art algorithms, self-adaptive control parameters in differential evolution (jDE), sequential DE enhanced by neighborhood search for large-scale global optimization (SDENS), and differential ant-stigmergy algorithm (DASA). These comparisons reveal that DEELS outperforms jDE and SDENS except DASA on the majority of test instances.