Pessimistic Bilevel Optimization: A Survey
- DOI
- 10.2991/ijcis.11.1.56How to use a DOI?
- Keywords
- Bilevel optimization; Pessimistic formulation; Stackelberg games
- Abstract
Bilevel optimization are often addressed in an organizational hierarchy in which the upper level decision maker is the leader and the lower level decision maker is the follower. The leader frequently cannot obtain complete information from the follower. As a result, the leader most tends to be risk-averse, and then would like to create a safety margin to bound the damage resulting from the undesirable selection of the follower. 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. Since to the best of our knowledge, there is not a comprehensive review on pessimistic bilevel optimization, the goal of this paper is to provide a extensive review on pessimistic bilevel optimization from basic definitions and properties to solution approaches. Some real applications are also proposed. This survey will directly support researchers in understanding theoretical research results, designing solution algorithms and applications in relation to pessimistic bilevel optimization.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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TY - JOUR AU - June Liu AU - Yuxin Fan AU - Zhong Chen AU - Yue Zheng PY - 2018 DA - 2018/03/09 TI - Pessimistic Bilevel Optimization: A Survey JO - International Journal of Computational Intelligence Systems SP - 725 EP - 736 VL - 11 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.11.1.56 DO - 10.2991/ijcis.11.1.56 ID - Liu2018 ER -