Research On Vehicle Routing Problem With Simultaneous Delivery And Pickup Aiming At The Lowest Cost Of Transportation

The traditional ways to increase profit by reducing resource consumption and improving labor productivity are getting harder and harder with the development of modernization and the progress of science and technology, modern logistics is an important mean to break the bottleneck, reasonable logistics planning can effectively reduce costs, improve efficiency, and gets more and more attention from the society. According to statistics, in 2015 the total social logistics cost accounted for 17% of GDP, and the transportation cost accounted for about 50% of the total logistics cost, then the reduction of transportation cost will bring huge economic benefits to the whole society. Therefore, it is necessary to concentrate on the reduction of the cost of transportation.For transportation, meeting customers’ needs, reasonable scheduling of vehicles and organizing travel route are the basic tasks, how to coordinate the completion of several tasks under certain constraints is the vehicle routing problem. Vehicle routing problem is an important aspect of modern transportation, and it is also the key research field for logistics experts at home and abroad. Reasonable vehicle routing planning can improve the transport efficiency and reduce the logistics cost, so it has important theoretical and practical significance for the research of vehicle routing problem.The traditional vehicle routing problem only considers the simple pickup or delivery process, not takes the pickup and delivery as a whole task into account. While the vehicle routing problem with simultaneous delivery and pickup does not care the order of pickup and delivery.Therefore, completing the task of pickup and delivery at the same time is a good way to avoid the roundabout transportation and repeated transportation, also it can reduce cost effectively and improve transport efficiency. By the way, VRPSDP is also the requirement of development of reverse logistics and green logistics.Usually, the research of VRPSDP is based on the shortest path to build the model, pursuing one-sided mileage minimization, or only considering one of the transportation cost+ when establish the lowest cost of vehicle routing model, these methods ignore the influence of other factors in the distribution process, they are ideal model. However, in the actual operation, and the transportation costs includes vehicle costs and indirect costs. Vehicle costs are composed of labor cost, fuel consumption, tire wear and tear, warranty cost, tax, loss of traffic accident, depreciation and so on. Indirect cost refers to various management costs and when organize the process of transport and distribution. Based on this idea, the shortest distance plan is not necessarily the lowest cost. So it is necessary to establish a vehicle routing optimization model considering all aspects of the transport cost synthetically to make the distribution plan more reasonable.Find out the factors which affect the vehicle routing choice through the analysis of transportation cost, then take labor cost, fuel consumption, tire cost, traffic accident loss and depreciation into consideration, at last build the vehicle routing optimization model based on the least cost. In the meanwhile propose improvement idea pointing at the capacity constraint and service time constraint of the node. VRPSDP is recognized as a NP hard problem, this article uses genetic algorithm to solve the problem based on MATLAB platform.In this paper, a vehicle routing optimization model based on the least cost is constructed, at the same time, it puts forward the idea of improving the capacity limit of VRPSDP. VRPSDP is recognized as a NP hard problem. It is optimized by genetic algorithm to solve the vehicle routing problem with genetic algorithm under MATLAB programming toolkit. Finally, two examples are used to verify the validity and rationality of the proposed VRPSDP model.