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Fuzzy programming approach to multi-objective stochastic linear programming problems
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DOI：10.1016/S0165-0114(96)00056-5.png)
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This paper presents an application of fuzzy programming approach to the multi-objective stochastic linear programming problem. After converting the proposed stochastic programming problem into a deterministic problem (which may be linear or non-linear), fuzzy programming approach is applied to find the compromise solution. Assuming the coefficients of the decision variables in the objective functions and in the constraints, and the right-hand-side parameters in the constraints as normal random variables, a methodology is presented to convert the probabilistic problem into a deterministic problem. Then fuzzy programming is applied using linear as well as non-linear membership functions. The method leads to an efficient solution as well as an optimal compromise solution. Numerical example is also presented to illustrate the methodology. (C) 1997 Elsevier Science B.V.
Keyword:
chance constrained programming
two-stage programming
fuzzy programming
linear and non-linear membership functions
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