stochastic/Probabilistic/fuzzy/dynamic modeling
Ali Mahmoodirad; Marzieh Salehi-Dareh-Barik; Rohollah Taghaodi
Abstract
Uncertainty is one of the most important factors which affect transportation models. As the value of most of the parameters in real-word problems are not clear, this paper represent a cost-based transportation problem with type-2 fuzzy parameters. Applying possibility theory, the fuzzy objective function ...
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Uncertainty is one of the most important factors which affect transportation models. As the value of most of the parameters in real-word problems are not clear, this paper represent a cost-based transportation problem with type-2 fuzzy parameters. Applying possibility theory, the fuzzy objective function and fuzzy constraints are formulated by a credibility measure. In addition, type-2 fuzzy variables are crisped using possibillistic critical value reduction method, in order to convert the main model into two mixed-integer sub-models which are solvable by a parametric programming approach. A numerical example including crisp demand and cost values but fixed and variable probability distributions is solved by the proposed approach. The results prove the effectiveness and flexibility of the proposed approach.