Hunan University of Business and Technology
Aiming at the actual situation of regional restrictions in some urban areas and the coexistence of fuel vehicles and electric vehicles in the logistics system, a programming model of the mixed fleet vehicle routing problem (MFVRP) is formulated by comprehensively considering the factors such as customer demand, service time, electric vehicles range, existing charging facilities, partial charging strategy, vehicle fuel consumption and carbon emissions. The goal of the MFVRP model is to minimize the sum of fixed cost of vehicles, driver salary, charging cost of electric vehicles, cost of fuel consumption and carbon emissions. An improved ant colony algorithm was designed to solve the problem according to the characteristics of the MFVRP model. The experiments were carried out with multiple types of instances. The experimental results show that the proposed methods can provide a satisfactory MFVRP solution that meets the goal of decision makers in very short time, effectively reduce the total distribution cost, reduce fuel consumption and carbon emissions. The proposed approaches are reasonable, feasible and effective.