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An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem

Author

Listed:
  • Tao Zhang
  • Tiesong Hu
  • Yue Zheng
  • Xuning Guo

Abstract

An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). For such problems, the proposed algorithm directly simulates the decision process of bilevel programming, which is different from most traditional algorithms designed for specific versions or based on specific assumptions. The BLMPP is transformed to solve multiobjective optimization problems in the upper level and the lower level interactively by an improved PSO. And a set of approximate Pareto optimal solutions for BLMPP is obtained using the elite strategy. This interactive procedure is repeated until the accurate Pareto optimal solutions of the original problem are found. Finally, some numerical examples are given to illustrate the feasibility of the proposed algorithm.

Suggested Citation

  • Tao Zhang & Tiesong Hu & Yue Zheng & Xuning Guo, 2012. "An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-13, April.
    • Handle: RePEc:hin:jnljam:626717
    DOI: 10.1155/2012/626717
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    Cited by:

    1. Yunjia Ma & Wei Xu & Lianjie Qin & Xiujuan Zhao, 2019. "Site Selection Models in Natural Disaster Shelters: A Review," Sustainability, MDPI, vol. 11(2), pages 1-24, January.
    2. Syed Mohd Muneeb & Ahmad Yusuf Adhami & Zainab Asim & Syed Aqib Jalil, 2019. "Bi-level decision making models for advertising allocation problem under fuzzy environment," 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. 10(2), pages 160-172, April.

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