Mixed-Energy Fleet Pollution-Routing Problem with Time Windows

Transportation activities have caused a large amount of energy consumption and environmental pollution. With increasing emphasis on environmental protection, transportation companies have to pay more attention to social benefits. At the same time, scorching competition has put forward a higher demand for customer satisfaction. This paper studies a pollution-routing problem (PRP) to minimize several pollutants emissions and find maximum improvements in delay time at customers based on soft time windows. The routing model focuses on a mixed-energy fleet, which introduces electric vehicles into a homogeneous combustion engine fleet. A Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted to find the Pareto-frontier of the PRP model. We investigate the effect of the electric vehicle's mileage on two objectives by sensitivity analysis to understand the problem better.