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A Possibilistic Programming Approach for Vehicle Routing Problem with Fuzzy Fleet Capacity (FCVRP)

Abstract

Seyed Mohammad Seyedhosseini

In this paper we present the vehicle routing problem with fuzzy fleet capacity (FCVRP) to find short routes with the minimal transportation cost. We propose a possibilistic 0-1 linear programming model to deal with such issues. To solve the proposed possibilistic optimization model, we apply an efficient possibilistic method proposed by Parra et al. [1] The FCVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, we develop a hybrid genetic algorithm (HGA). For the model verification, some small, medium and large-scale test problems are solved by HGA and the results are compared with obtained results from Lingo 9.0. Finally, we do a case study in the Kalleh Company in Amol and publish the results.

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