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An improved artificial bee colony with modified augmented Lagrangian for constrained optimization

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Abstract

Artificial bee colony (ABC) algorithm has been successfully applied to solve constrained optimization problems (COPs). However, it is noteworthy that when using ABC to deal with COPs, the commonly used constraint-handling technique is the Deb’s feasibility-based rules. To our limited knowledge, the present ABC and its variants with augmented Lagrangian (AL) multiplier method have not been found applications to the COPs. In this paper, a novel constrained optimization method, named IABC-MAL, which integrates the benefit of the improved ABC (IABC) algorithm capability for obtaining the global optimum with the modified AL (MAL) method to handle constraints. This paper presents the first effort to integrate ABC algorithm with the AL method. To verify the performance of the proposed IABC-MAL, 24 well-known benchmark test problems at CEC2006, 18 benchmark test problems at CEC2010, and 5 engineering design problems are employed. Experiment results demonstrate that the proposed IABC-MAL algorithm shows better performance in comparison with other state-of-the-art algorithms from the literature.

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Acknowledgements

The authors thank the anonymous reviewers for their very helpful and constructive comments and suggestions. This work was supported in part by the National Natural Science Foundation of China under Grant No. 61463009, the Science and Technology Foundation of Guizhou Province under Grant No. [2016]1022, the project of high-level creative talents in Guizhou province Grant No. 20164035, and the Central Support Local Projects under Grant No. PXM 2013-014210-000173.

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Authors and Affiliations

  1. Guizhou Key Laboratory of Economics System Simulation, Guizhou University of Finance and Economics, Guiyang, 550025, China

    Wen Long, Shaohong Cai & Wenzhuan Zhang

  2. School of Science, Beijing University of Civil Engineering and Architecture, Beijing, 100083, China

    Ximing Liang

  3. School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang, 550025, China

    Jianjun Jiao

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  1. Wen Long
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  2. Ximing Liang
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  3. Shaohong Cai
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  4. Jianjun Jiao
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  5. Wenzhuan Zhang
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Correspondence to Ximing Liang.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors.

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Communicated by V. Loia.

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Long, W., Liang, X., Cai, S. et al. An improved artificial bee colony with modified augmented Lagrangian for constrained optimization. Soft Comput 22, 4789–4810 (2018). https://doi.org/10.1007/s00500-017-2665-9

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