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Methods for Pessimistic Bilevel Optimization

In: Bilevel Optimization

Author

Listed:
  • June Liu

    (Huaibei Normal University)

  • Yuxin Fan

    (Huazhong University of Science and Technology)

  • Zhong Chen

    (Yangtze University)

  • Yue Zheng

    (Huaibei Normal University)

Abstract

Pessimistic bilevel optimization represents an attractive tool to model risk-averse hierarchy problems, and would provide strong ability of analysis for the risk-averse leader. The goal of this chapter is to provide a extensive review on pessimistic bilevel optimization from basic models, definitions and properties to solution approaches. It will directly support researchers in understanding theoretical research results, designing solution algorithms in relation to pessimistic bilevel optimization.

Suggested Citation

  • June Liu & Yuxin Fan & Zhong Chen & Yue Zheng, 2020. "Methods for Pessimistic Bilevel Optimization," Springer Optimization and Its Applications, in: Stephan Dempe & Alain Zemkoho (ed.), Bilevel Optimization, chapter 0, pages 403-420, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-52119-6_14
    DOI: 10.1007/978-3-030-52119-6_14
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    Cited by:

    1. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.

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