| A particle swarm optimization based algorithm for fuzzy bilevel decision making with constraints-shared followers |
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Symposium on Applied Computing
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Proceedings of the 2009 ACM symposium on Applied Computing
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Honolulu, Hawaii
SESSION: Applications of evolutionary computation track
table of contents
Pages 1075-1079
Year of Publication: 2009
ISBN:978-1-60558-166-8
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Authors
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Ya Gao
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University of Technology, Sydney, NSW, Australia
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Guangquan Zhang
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University of Technology, Sydney, NSW, Australia
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Jie Lu
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University of Technology, Sydney, NSW, Australia
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ABSTRACT
In a bilevel decision problem, decision making may involve multiple followers and fuzzy demands. This research focuses on the problem of fuzzy linear bilevel decision making with multiple followers who share common constraints (FBCSF). Based on the ranking relationship among fuzzy sets defined by cut set and satisfactory degree α, a FBCSF model is presented and a particle swarm optimization based algorithm is developed. The experiments reveal that solutions obtained by this algorithm are reasonable and stable.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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