Sequential quadratic programming enhanced backtracking search algorithm

Wenting ZHAO, Lijin WANG, Yilong YIN, Bingqing WANG, Yuchun TANG

Front. Comput. Sci. ›› 2018, Vol. 12 ›› Issue (2) : 316-330.

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Front. Comput. Sci. ›› 2018, Vol. 12 ›› Issue (2) : 316-330. DOI: 10.1007/s11704-016-5556-9
RESEARCH ARTICLE

Sequential quadratic programming enhanced backtracking search algorithm

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Abstract

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.

Keywords

numerical optimization / backtracking search algorithm / sequential quadratic programming / local search

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Wenting ZHAO, Lijin WANG, Yilong YIN, Bingqing WANG, Yuchun TANG. Sequential quadratic programming enhanced backtracking search algorithm. Front. Comput. Sci., 2018, 12(2): 316‒330 https://doi.org/10.1007/s11704-016-5556-9

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