A multi-objective Two-Echelon Capacitated Vehicle Routing Problem for perishable products

This article addresses a general tri-objective two-echelon capacitated vehicle routing problem (2E-CVRP) to minimize the total travel cost, customers waiting times and carbon dioxide emissions simultaneously in distributing perishable products. In distributing perishable products, customers’ satisfaction is very important and is inversely proportional to the customers waiting times. The proposed model is a mixed integer non-linear programming (MINLP). By applying some linearization methods, the MINLP model exchanged to a mixed integer linear programming (MILP). This paper uses a non-dominated sorting genetic (NSGA-II) algorithm to solve the presented mathematical model. The related results would be compared with Lp-metric results in small-sized test problems and with multi objective particle swarm optimization (MOPSO) algorithm in medium and large sized test problems. In order to evaluate the quality of the solution sets, the results of two metaheuristic algorithms are compared based on four comparison metrics in medium sized problems. The obtained results indicate the efficiency of the NSGA-II algorithm.