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A Comprehensive Multi-Strategy Enhanced Biogeography-Based Optimization Algorithm for High-Dimensional Optimization and Engineering Design Problems

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  • Chenyang Gao

    (School of Computer Science and Engineering, Xidian University, Xi’an 710071, China)

  • Teng Li

    (School of Computer Science and Engineering, Xidian University, Xi’an 710071, China)

  • Yuelin Gao

    (School of Computer Science and Engineering, Xidian University, Xi’an 710071, China
    Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Yinchuan 750021, China)

  • Ziyu Zhang

    (Ningxia Province Key Laboratory of Intelligent Information and Data Processing, North Minzu University, Yinchuan 750021, China)

Abstract

The biogeography-based optimization (BBO) algorithm is known for its simplicity and low computational overhead, but it often struggles with falling into local optima and slow convergence speed. Against this background, this work presents a multi-strategy enhanced BBO variant, named MSBBO. Firstly, the example chasing strategy is proposed to eliminate the destruction of the inferior solutions to superior solutions. Secondly, the heuristic crossover strategy is designed to enhance the search ability of the population. Finally, the prey search–attack strategy is used to balance the exploration and exploitation. To verify the performance of MSBBO, we compare it with standard BBO, seven BBO variants (PRBBO, BBOSB, HGBBO, FABBO, BLEHO, MPBBO and BBOIMAM) and seven meta-heuristic algorithms (GWO, WOA, SSA, ChOA, MPA, GJO and BWO) on multiple dimensions of 24 benchmark functions. It concludes that MSBBO significantly outperforms all competitors both on convergence accuracy, speed and stability, and MSBBO basically converges to the same results on 10,000 dimensions as on 1000 dimensions. Further, MSBBO is applied to six real-world engineering design problems. The experimental results show that our work is still more competitive than other latest optimization techniques (COA, EDO, OMA, SHO and SCSO) on constrained optimization problems.

Suggested Citation

  • Chenyang Gao & Teng Li & Yuelin Gao & Ziyu Zhang, 2024. "A Comprehensive Multi-Strategy Enhanced Biogeography-Based Optimization Algorithm for High-Dimensional Optimization and Engineering Design Problems," Mathematics, MDPI, vol. 12(3), pages 1-35, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:3:p:435-:d:1329080
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    References listed on IDEAS

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    2. Martín Montes Rivera & Carlos Guerrero-Mendez & Daniela Lopez-Betancur & Tonatiuh Saucedo-Anaya, 2023. "Dynamical Sphere Regrouping Particle Swarm Optimization: A Proposed Algorithm for Dealing with PSO Premature Convergence in Large-Scale Global Optimization," Mathematics, MDPI, vol. 11(20), pages 1-40, October.
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    4. Xiao Sang & Xiyu Liu & Zhe Zhang & Lin Wang, 2021. "Improved Biogeography-Based Optimization Algorithm by Hierarchical Tissue-Like P System with Triggering Ablation Rules," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-24, March.
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