Vehicle Routing Problem with Time Windows for Reducing Fuel Consumption

Abstract

Most of the studies on vehicle routing problem with time windows (VRPTW) aim to minimize total travel distance or travel time. This paper presents the VRPTW with a new objective function of minimizing the total fuel consumption. A mathematical model is proposed to formulate this problem. Then, a novel tabu search algorithm with a random variable neighborhood descent procedure (RVND) is given, which uses an adaptive parallel route construction heuristic, introduces six neighborhood search methods and employs a random neighborhood ordering and shaking mechanisms. Computational experiments are performed on realistic instances which shed light on the tradeoffs between various parameters such as total travel distance, total travel time, total fuel consumption, number of vehicles utilized and total wait time. The results show that the solution of minimizing total fuel consumption has the potential of saving fuel consumption contrary to the solution of the traditional VRPTW, and is beneficial to develop environmental-friendly economies.