Abstract
To provide an optimal products distribution system, it is important to consider the cost of transportation and customer satisfaction and provide timely services to them. In this paper, in order to deal with the mentioned challenges, a two-objective mathematical model of the problem of routing an inhomogeneous electric vehicle with a time window with the possibility of recharging is presented. In the proposed model, in addition to the objective function of minimizing the route traveled and the costs associated with vehicles, a soft time window is provided for vehicles to reach the destination depot to minimize their latency in a separate objective function. Moreover, this objective function will lead to vehicles arriving at customer points sooner and will increase their satisfaction. To solve the proposed mathematical model, the epsilon constraint method is used to achieve the exact solutions and due to the NP-hard nature of the mathematical model, the multi objective particle swarm optimization (MOPSO) algorithm is used to solve the model in large scale. The results of numerical comparisons show that the MOPSO algorithm can show high efficiency in finding Pareto solutions.
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