A decomposition-based differential evolution with reinitialization for nonlinear equations systems

被引:29
作者
Liao, Zuowen [1 ]
Gong, Wenyin [1 ]
Wang, Ling [2 ]
Yan, Xuesong [1 ]
Hu, Chengyu [1 ]
机构
[1] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Peoples R China
[2] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
Nonlinear equations systems; Decomposition technique; Reinitialization; Sub-population control strategy; Differential evolution; MULTIPLE OPTIMAL-SOLUTIONS; GLOBAL OPTIMIZATION; MULTIOBJECTIVE OPTIMIZATION; ALGORITHM; ROOTS;
D O I
10.1016/j.knosys.2019.105312
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Solving nonlinear equations systems (NESS) is one of the most important challenges in numerical computation, especially to find multiple roots in one run. In this paper, a decomposition-based differential evolution with reinitialization is proposed to tackle this challenging task. The main advantages of our method are: (i) an improved parameter-free decomposition technique is exploited to partition the population into numerous sub-populations to locate multiple roots of NESs; (ii) to enhance the search ability of optimization algorithm, a sub-population control strategy is presented to control the number of solutions in the sub-populations; and (iii) the sub-population reinitialization mechanism is proposed to enrich the population diversity. To evaluate the performance of our approach, thirty NES problems with different characteristics are selected as the test suite. Moreover, to further indicate the superiority of our method, ten complex NESs with many roots are also tested. Experimental results show that the proposed approach can locate multiple roots in a single run. In addition, it is able to obtain better results compared with other state-of-the-art methods in terms of both root rate and success rate. (C) 2019 Elsevier B.V. All rights reserved.
引用
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页数:12
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