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Constrained Laplacian biogeography-based optimization algorithm

Author

Listed:
  • Vanita Garg

    (Indian Institute of Technology)

  • Kusum Deep

    (Indian Institute of Technology)

Abstract

Biogeography-based optimization (BBO) is a relatively new nature inspired optimization technique proposed by Dan Simon for unconstrained optimization, which was later generalized and improved by Happing Ma and Dan Simon for constrained optimization, called blended biogeography-based optimization. In an earlier paper, the authors have proposed a Laplacian biogeography-based optimization algorithm (LX-BBO) for unconstrained optimization. The purpose of the present paper is to generalize the LX-BBO from the unconstrained case to the constrained case. This is done by using the Deb’s constrained handling method. In order to evaluate the performance of the proposed constrained LX-BBO for constrained optimization problems, five different constrained optimization problems and popular CEC 2006 benchmark collection is used. Based on the analysis of results it is shown that the proposed Constrained LX-BBO outperforms Blended BBO for constrained optimization.

Suggested Citation

  • Vanita Garg & Kusum Deep, 2017. "Constrained Laplacian biogeography-based optimization algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 867-885, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0539-7
    DOI: 10.1007/s13198-016-0539-7
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    Cited by:

    1. Mousumi Banerjee & Vanita Garg & Kusum Deep, 2023. "Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 307-327, March.
    2. Eryang Guo & Yuelin Gao & Chenyang Hu & Jiaojiao Zhang, 2023. "A Hybrid PSO-DE Intelligent Algorithm for Solving Constrained Optimization Problems Based on Feasibility Rules," Mathematics, MDPI, vol. 11(3), pages 1-34, January.

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