Design of a hybridization between Tabu search and PAES algorithms to solve a multi-depot, multi-product green vehicle routing problem

Abstract

Vehicle routing problem (VRP) is a classic problem studied in logistic. One of the most important variations within this problem is called Green Vehicle Routing Problem (GVRP), in which environmental aspects are considered when designing product delivery routes. This variant arises due to the high levels of pollution produced by transport vehicles, so it is a variation whose study represents a vital impact nowadays. This project will consider a GVRP and will be developed considering the characteristics of multi-depot (MDVRP) and multi-product (MPVRP) to minimize the costs of assignation of vehicles and CO2 emissions. To solve the problem, this project proposes a hybridization between the classic tabu search (TS) metaheuristic and the PAES algorithm (TS+PAES) to generate the Pareto frontier of both objectives. An integer mixed linear programming model is formulated and developed for each objective function separately to have an optimal point of comparison for the efficiency of the proposed algorithm. Also, the TS+PAES algorithm is compared to the nearest neighbor algorithm for large instances. Two computational experiments were carried out, one for small and the other one for large instances. The experiment for small instances showed that the GAP of each extreme of the frontier compared to the MILP model is on average 0.73%. For large instances, the metaheuristic improves in 0.1% the results presented by the MILP model showing that the metaheuristic provides closer near-optimal solutions in less computational time. Besides, the metaheuristic, in comparison with the nearest neighborhood heuristic, improves in 44.21% the results of emissions and in 3.88% the costs. All these results demonstrate the effectiveness of the metaheuristic.