Research And Application Of Fleet Size And Mix Vehicle Routing Problem

With global warming, reducing energy consumption and controlling carbon emissions are becoming increasingly serious. Logistics industry which has bigger total energy consumption should undertake the responsibility of energy conservation and emission reduction. Low carbon logistics emerges in order to change its extensive operation. Distribution is an important part of logistics, and there still exists unreasonable phenomenon such as the return or leave empty transport, cross transport, roundabout transport, repeated transport during transportation. So energy consumption can not be ignored, it is necessary to optimize the distribution routes, and it will be better to consider energy consumption as one of the optimization objectives.But in the actual distribution, types of vehicles are more than one, and different types mean different loading capacity, different fixed cost and different vehicle distance traveled. Then Fleet Size and Mix Vehicle Routing Problem (FSMVRP) is more practical. Naturally fleet size and mix vehicle routing problem with consideration of energy consumption become the focus of this paper. It also will be instructive to further researches and practice.This paper firstly summarized overseas and domestic research status of FSMVRP, and focused on the analysis of FSMVRP in the elements, mathematical models and algorithms. Genetic algorithm because of its strong robustness, global convergence, easy to operate and less used in FSMVRP is chosen for this paper. Then combined with the theory of low energy consumption, the model was built based on the sum of energy costs associated with the vehicle types and fixed costs as the optimization objective, which also called Fleet Size and Mix Vehicle Routing Problem with Energy Minimizing (FSMVRPEM). In order to verify the feasibility and effectiveness of improved genetic algorithm, experiments on benchmark are showed with competitive results. Finally FSMVRPEM is applied to FMCG (Fast Moving Consumer Goods) distribution center, which has dense retail distribution network, small but steady demand. So the fixed routes distribution plans are made at present. According to this the paper starting from the whole, optimized routes spread over the central city.The result is a reasonable solution which not only reduce vehicle use, but also improve the service level.Further, because of the convenience of data access and the feasibility and effectiveness of algorithm, FSMVRPEM is a better decision-making tool for vehicle scheduling and route optimization. Fleet selection algorithm implemented in simple and effective way needs to be discussed further, and the application of FSMVRPEM in large-scale real problem requires much attention.