A multi-criteria optimization model for emission-concerned multi-depot vehicle routing problem with heterogeneous fleet

Not only greenhouse gases but also other air pollutant emissions from transportation have direct impacts on the environment and human health. The challenge of solving the conflict between profit and environmental consequences in logistics has motivated many studies on the vehicle routing problem. In this paper, a multiobjective mixed integer linear programming model is proposed to minimize transportation expenses and pollutant emissions for the multi-depot heterogeneous vehicle routing problem. A metaheuristic is adapted to obtain the Pareto optimal solutions. After a search procedure, decision makers are able to choose among best transportation plans that balance many objectives at once including economic benefits and environmental impacts. Computational experiments are performed on seven well-known benchmark problem sets. The results demonstrate the existence of greener transportation plans, which are illustrated alongside the best solutions previously reported. The study shows that, in return for a minimal economic tradeoff, a substantial amount of pollution could be avoided.