Fuzzy Bi-level Decision-Making Techniques: A Survey
- https://doi.org/10.1080/18756891.2016.1180816How to use a DOI?
- Bi-level decision-making, bi-level programming, fuzzy sets, fuzzy systems, decision support systems
Bi-level decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a bi-level hierarchy. A challenge in handling bi-level decision problems is that various uncertainties naturally appear in decision-making process. Significant efforts have been devoted that fuzzy set techniques can be used to effectively deal with uncertain issues in bi-level decision-making, known as fuzzy bi-level decision-making techniques, and researchers have successfully gained experience in this area. It is thus vital that an instructive review of current trends in this area should be conducted, not only of the theoretical research but also the practical developments. This paper systematically reviews up-to-date fuzzy bi-level decision-making techniques, including models, approaches, algorithms and systems. It also clusters related technique developments into four main categories: basic fuzzy bi-level decision-making, fuzzy bi-level decision-making with multiple optima, fuzzy random bi-level decision-making, and the applications of bi-level decision-making techniques in different domains. By providing state-of-the-art knowledge, this survey paper will directly support researchers and practitioners in their understanding of developments in theoretical research results and applications in relation to fuzzy bi-level decision-making techniques.
- © 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
Cite this article
TY - JOUR AU - Guangquan Zhang AU - Jialin Han AU - Jie Lu PY - 2016 DA - 2016/04 TI - Fuzzy Bi-level Decision-Making Techniques: A Survey JO - International Journal of Computational Intelligence Systems SP - 25 EP - 34 VL - 9 IS - Supplement 1 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2016.1180816 DO - https://doi.org/10.1080/18756891.2016.1180816 ID - Zhang2016 ER -