Using Fuzzy Goal Programming Technique to Solve Multiobjective Chance Constrained Programming Problems in a Fuzzy Environment

In this paper a fuzzy goal programming technique is presented to solve multiobjective decision making problems in a probabilistic decision making environment where the right sided parameters associated with the system constraints are exponentially distributed fuzzy random variables. In model formula...

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Bibliographic Details
Published in:International journal of fuzzy system applications Vol. 2; no. 1; pp. 71 - 80
Main Authors: Biswas, Animesh, Modak, Nilkanta
Format: Journal Article
Language:English
Published: Hershey IGI Global 01.01.2012
Subjects:
Constraints
Decision making
Fuzzy logic
Fuzzy sets
Goal programming
Mathematical models
Methods
Multiple objective analysis
Parameters
Random variables
India
ISSN:2156-177X, 2156-1761
Online Access:Get full text
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Summary:In this paper a fuzzy goal programming technique is presented to solve multiobjective decision making problems in a probabilistic decision making environment where the right sided parameters associated with the system constraints are exponentially distributed fuzzy random variables. In model formulation of the problem, the fuzzy chance constrained programming problem is converted into a fuzzy programming problem by using general chance constrained methodology. Then by realizing the fuzzy nature of the parameters associated with the system constraints, the problem is decomposed by considering the tolerance ranges of the parameters. The tolerance membership functions of each of the individual objectives are defined in isolation to measure the degree of achievements of the goal levels of the objectives. Then a fuzzy goal programming model is developed to achieve the highest degree of each of the defined membership functions to the extent possible. In the solution process the minsum fuzzy goal programming technique is used to find the most satisfactory decision in the decision making environment. An example is solved to illustrate the proposed methodology and the achieved solution is compared with the solution of another existing technique.
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ISSN:2156-177X
2156-1761
DOI:10.4018/ijfsa.2012010105