Abstract
Transport logistics and fleet management problems often fall into one class of the optimization problems. Finding an optimal set of routes for a group of vehicles in the transportation network under defined constraints is known as the Vehicle Routing Problem (VRP). In this paper, we propose a novel hybrid uncertain approach, in which first considers a capacitated VRP whose demands are assumed to be fuzzy random variables. Then the crisp equivalent model is presented as a nonlinear mixed integer programming, to manage the problem. Since the resulted problem formulation is NP-Hard, we use tabu search method and compare the results with the optimal solutions. The usefulness of the model is validated by its application to a real-world problem and comparing the results with the current status. The results indicate that the proposed model can provide a practical tool to significantly reduce the cost of logistic.
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