A transportation problem is one of the most important issues in a supply chain, and one of its branches is a fixed-charge transportation problem (FCTP). The FCTP is an NP- problem and can be formulated as an integer programming model and solved. The purpose of this paper is to develop an effective and efficient method to solve this problem. Therefore, at first, this problem will be formulated by integer programming. Then, for solving this problem, various algorithms such as genetic algorithm, simulated annealing and firefly are used. A new solution presentation for the proposed algorithm is presented. By using these algorithms having the good performance such as time calculations, memory required for calculations, and the ability to find global optimal solution when you get a computer, several examples have been solved. In fact, initially, by using the Taguchi experimental design, parameters in algorithms are adjusted and set the best option for each of the determined parameters, and then the algorithm performance is examined. Finally, to make comparisons between the three proposed algorithms, several test problems in small and large sizes are produced. It is concluded that the objective function value and computational time in the genetic algorithm is less in order to obtain a near-optimal solution.
 

Keywords: Fixed-charge transportation, Meta-heuristics, Fuzzy environment, Taguchi experimental design

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