Sequential quadratic programming enhanced backtracking search algorithm

被引:0
|
作者
Wenting Zhao
Lijin Wang
Yilong Yin
Bingqing Wang
Yuchun Tang
机构
[1] Shandong University,School of Computer Science and Technology
[2] Fujian Agriculture and Forestry University,College of Computer and Information Science
[3] Shandong University School of Medicine,Research Center for Sectional and Imaging Anatomy
来源
关键词
numerical optimization; backtracking search algorithm; sequential quadratic programming; local search;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper, we propose a new hybrid method called SQPBSA which combines backtracking search optimization algorithm (BSA) and sequential quadratic programming (SQP). BSA, as an exploration search engine, gives a good direction to the global optimal region, while SQP is used as a local search technique to exploit the optimal solution. The experiments are carried on two suits of 28 functions proposed in the CEC-2013 competitions to verify the performance of SQPBSA. The results indicate the proposed method is effective and competitive.
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页码:316 / 330
页数:14
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