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α-Satisfactory goal programming method for multi-objective optimization with priorities and fuzzy parameters.
- Source :
-
Journal of Intelligent & Fuzzy Systems . 2019, Vol. 37 Issue 4, p5167-5178. 12p. - Publication Year :
- 2019
-
Abstract
- In this paper, the α-satisfactory goal programming (GP) method is proposed for multi-objective optimization (MOO) with priorities and fuzzy parameters. Fuzzy parameters are treated as fuzzy numbers, and all objectives are modeled into fuzzy goals over α-level sets. The order of α-satisfactory degrees is applied to preemptive priority requirement, where the objectives with higher priority can achieve the higher α-satisfactory degree. In order to guarantee the feasibility and seek the preferred solution, a priority variable is introduced to relax the strict order. For three fuzzy relations, GP is combined with the relaxed order constraint to formulate the different α-satisfactory optimization models. By regulating optimization parameters λ and α, the most satisfactory solution over fuzzy parameters can be obtained, and the balance between optimization and priority can be realized. The reformulated α-GP models are proved to be feasible, and their solutions are guaranteed to be M-α-Pareto optimal by the test model. In order to decrease optimization burden, the algorithm to compute the α-maximum regulating parameter is proposed, by which the bound of λ can be determined. The effectiveness of the proposed method is well demonstrated by numerical examples. [ABSTRACT FROM AUTHOR]
- Subjects :
- *GOAL programming
Subjects
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 37
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 139366310
- Full Text :
- https://doi.org/10.3233/JIFS-18904