A differential evolution algorithm to solve new green VRP model by optimizing fuel consumption considering traffic limitations for collection of expired products

The purpose of this research is to present a new mathematical modeling for a vehicle routing problem considering concurrently the criteria such as distance, weight, traffic considerations, time window limitation, and heterogeneous vehicles in the reverse logistics network for collection of expired products. In addition, we aim to present an efficient solution approach according to differential evolution (DE) procedure to solve such a complicated problem. By using mathematical modeling tools for formulating the environmental sensitivities in vehicle routing problems, the reverse logistics must be managed according to criteria such as cargo weight carried by the vehicle, the vehicle speed and the covered distance by the vehicle. This leads to optimization and reduction of transportation fuel consumption and hence reduction of air pollution and environment concerns. This concept has led to creation and study of the green vehicle routing problems in this paper.Numerical analysis indicates that performance of the proposed DE algorithm can be validated in terms of CPU run time and optimality gap for solving the proposed model. Furthermore, sensitivity analysis show that extending maximum travelling distance by each vehicle, and increasing capacity of vehicles lead to reduction of total cost in the problem.