Study Of Common-split Delivery Vehicle Routing Problem

Since the beginning of the 21st century,with the continuous development of urbanization in China,the number and density of urban population have been increasing rapidly,and the proportion of urban trade has played a larger and growing percentage.The growing trade demand brings the economic development of the city,but also creates a lot of pressure to the urban delivery.The low loading rate of the delivery vehicle is a very serious problem,which causes the high logistics cost in cities and exacerbates the city’s traffic congestion as well as vehicle exhaust pollution and noise pollution,all these is crying that the current traditional urban delivery method can no longer satisfy the rapidly changing customer demand.Common Delivery has become one of the developing trends of urban delivery because of its significant economic and social benefits,which improves the utilization of logistics resources by increasing the volume of distribution and easing urban traffic pressure in the meantime.In the search of VRP whose customers’ demand can be split(SDVRP),by allowing a customer to be served by more than one vehicle,the SDVRP can save vehicle numbers and reduce total route length.Based on the study of predecessors,this paper proposes a Common Split Delivery Vehicle Routing Problem(CSDVRP),mainly:(1)Defines C SDVRP based on the background of Common Delivery and Split Delivery vehicle routing problem,analyzes the possibility of splitting customers’demand and the mix-relationship of different goods under Common Delivery,and also elaborates the costs of CSDVRP.(2)Establishes the model of Common Split Delivery Vehicle Routing Problem and analyzes the components of the model’s objective function(total cost)by providing the calculation method of each sub-cost.(3)Uses the Improved-Optimal Insertion Algorithm and Tabu Search Algorithm to solve the CSDVRP model.The application results verify the validity of the model,sensitivity analysis result shows that CSDVRP can save more cost by reducing the cost of order splitting.