Decentralized multi-objective bilevel decision making with fuzzy demands
Decisions in a decentralized organization often involve two levels. The leader at the upper level attempts to optimize his/her objective but is affected by the follower; the follower at the lower level tries to find an optimized strategy according to each of possible decisions made by the leader. Wh...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2007
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| Online Access: | http://hdl.handle.net/20.500.11937/20883 |
| _version_ | 1848750434483699712 |
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| author | Zhang, G. Lu, J. Dillon, Tharam S. |
| author_facet | Zhang, G. Lu, J. Dillon, Tharam S. |
| author_sort | Zhang, G. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Decisions in a decentralized organization often involve two levels. The leader at the upper level attempts to optimize his/her objective but is affected by the follower; the follower at the lower level tries to find an optimized strategy according to each of possible decisions made by the leader. When model a real-world bilevel decision problem, it also may involve fuzzy demands which appear either in the parameters of objective functions or constraints of the leader or the follower or both. Furthermore, the leader and the follower may have multiple conflict objectives that should be optimized simultaneously in achieving a solution. This study addresses both fuzzy demands and multi-objective issues and propose a fuzzy multi-objective bilevel programming model. It then develops an approximation branch-and-bound algorithm to solve multi-objective bilevel decision problems with fuzzy demands. Finally, two case-based examples further illustrate the proposed model and algorithm. |
| first_indexed | 2025-11-14T07:36:46Z |
| format | Journal Article |
| id | curtin-20.500.11937-20883 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:36:46Z |
| publishDate | 2007 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-208832018-03-29T09:06:34Z Decentralized multi-objective bilevel decision making with fuzzy demands Zhang, G. Lu, J. Dillon, Tharam S. Decisions in a decentralized organization often involve two levels. The leader at the upper level attempts to optimize his/her objective but is affected by the follower; the follower at the lower level tries to find an optimized strategy according to each of possible decisions made by the leader. When model a real-world bilevel decision problem, it also may involve fuzzy demands which appear either in the parameters of objective functions or constraints of the leader or the follower or both. Furthermore, the leader and the follower may have multiple conflict objectives that should be optimized simultaneously in achieving a solution. This study addresses both fuzzy demands and multi-objective issues and propose a fuzzy multi-objective bilevel programming model. It then develops an approximation branch-and-bound algorithm to solve multi-objective bilevel decision problems with fuzzy demands. Finally, two case-based examples further illustrate the proposed model and algorithm. 2007 Journal Article http://hdl.handle.net/20.500.11937/20883 10.1016/j.knosys.2007.01.003 Elsevier restricted |
| spellingShingle | Zhang, G. Lu, J. Dillon, Tharam S. Decentralized multi-objective bilevel decision making with fuzzy demands |
| title | Decentralized multi-objective bilevel decision making with fuzzy demands |
| title_full | Decentralized multi-objective bilevel decision making with fuzzy demands |
| title_fullStr | Decentralized multi-objective bilevel decision making with fuzzy demands |
| title_full_unstemmed | Decentralized multi-objective bilevel decision making with fuzzy demands |
| title_short | Decentralized multi-objective bilevel decision making with fuzzy demands |
| title_sort | decentralized multi-objective bilevel decision making with fuzzy demands |
| url | http://hdl.handle.net/20.500.11937/20883 |