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
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Abstract 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.
AbstractList 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.
Author Lu, Jie
Wu, Fengjie
Zhang, Guangquan
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10.1080/00207727808941724
10.1016/0165-0114(78)90031-3
10.1016/0165-0114(92)90318-X
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Issue 1
Keywords Fuzzy multiple objective linear programming
Approximate algorithm
Decision support technology
Optimization
Membership function
Optimization method
Multiobjective programming
Linear programming
Fuzzy programming
Multiple decision
Fuzzy algorithm
Applied mathematics
Decision aid
Algorithm analysis
Mathematical programming
Language English
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Snippet Many business decision problems involve multiple objectives and can thus be described by multiple objective linear programming (MOLP) models. When a MOLP...
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SubjectTerms Approximate algorithm
Calculus of variations and optimal control
Decision support technology
Exact sciences and technology
Fuzzy multiple objective linear programming
Mathematical analysis
Mathematics
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming, optimization and calculus of variations
Optimization
Sciences and techniques of general use
Title A new approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters
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