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A new approximate algorithm for solving multiple objective linear programming problems with fuzzy parameters
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DOI：10.1016/j.amc.2005.04.106.png)
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Abstract
En 中文
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. (c) 2005 Elsevier Inc. All rights reserved.
Keywords:
optimization
decision support technology
fuzzy multiple objective linear programming
approximate algorithm
Journal
IF:
3.4
Papers:
2.3W
Citations:
3.3W
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