A new approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters

Many business decision problems involve multiple objectives and can thus be described by multiple objective linear programming (MOLP) models. When a MOLP problem is being formulated, the parameters of objective functions and constraints are normally assigned by experts. In most real situations, the...

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Veröffentlicht in:Applied mathematics and computation Jg. 174; H. 1; S. 524 - 544
Hauptverfasser: Wu, Fengjie, Lu, Jie, Zhang, Guangquan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY Elsevier Inc 01.03.2006
Elsevier
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ISSN:0096-3003, 1873-5649
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Zusammenfassung:Many business decision problems involve multiple objectives and can thus be described by multiple objective linear programming (MOLP) models. When a MOLP problem is being formulated, the parameters of objective functions and constraints are normally assigned by experts. In most real situations, the possible values of these parameters are imprecisely or ambiguously known to the experts. Therefore, it would be more appropriate for these parameters to be represented as fuzzy numerical data that can be represented by fuzzy numbers. In this paper, a new approximate algorithm is developed for solving fuzzy multiple objective linear programming (FMOLP) problems involving fuzzy parameters in any form of membership functions in both objective functions and constraints. A detailed description and analysis of the algorithm are supplied. In addition, an example is given to illustrate the approximate algorithm.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2005.04.106