A model for capacitated green vehicle routing problem with the time-varying vehicle speed and soft time windows

Abstract

This paper investigates the capacitated green vehicle routing problem (GVRP) with time-varying vehicle speed and soft time windows. The GVRP is developed as a multi-objective mixed integer nonlinear programming (MINLP) model that incorporates a fuel consumption calculation algorithm. The proposed model considers the vehicle load and capacity as well as time-varying speed in order to account for traffic congestion. An improved non-dominated sorting genetic algorithm (NSGA-II) with adaptive strategies and greedy strategies is developed to solve the GVRP. The results of numerical experiments show that the consumption of fuel in a supply chain can be decreased sharply without any significant loss in customer satisfaction. The proposed NSGA-II has a better capability and efficiency than the original NSGA-II. Our experiments also indicate that the proposed model outperforms most of the best-known solutions obtained from the traditional modeling approaches.