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Abstract
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In this paper, we present a fuzzy goal programming model for Transportation Planning Decisions (TPD) problem. In real-world applications of the transportation planning decisions problems with multi-objective, input data or related parameters are majority vague/fuzzy. It is hard for decision maker(s) to determine the goal value of each objective precisely as the goal values are imprecise. We consider three methods in the research for solving TPD problem under fuzziness, first method is interactive fuzzy goal programming (IFGP), that this approach aim minimizing the worst upper bound to determine an reasonable solution which is end to the best lower bound of each objective function. Second method is fuzzy goal programming, that this procedure proposed a weighted additive model to solve TPD problem which uses flexibility to obtain the priority of fuzzy goals. We will consider Fuzzy Mix Integer Goal Programming (FMIGP) model in TPD problem, using linear membership functions and determining aspiration levels, therefore defuzzify with mix integer mathematical programming model. In last section of solution procedure, this model will solve by the software LINGO. Third procedure is interactive fuzzy linear programming (i-FMOLP); the aim of presented i-FMOLP method wills both costs and delivery time possibility minimizes. In this approach performance is experimented by measuring the degree of closeness of the compromise solution to the ideal solution using a family distance functions. In addition, this research shows that the interactive fuzzy linear programming (i-FMOLP) more performance relativity with other procedures.
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