Optimization Of Multi-depot Vehicle Routing Problem Of Company Y

Since the 1990 s,with the development of science and technology and the application of the Internet and big data,China's logistics industry has developed rapidly.Nowadays,the level of development of the logistics industry is a key factor that reflects the degree of modernization and comprehensive national strength.However,China's logistics development is still facing problems such as high logistics costs and low efficiency.Logistics distribution is an important part of the logistics industry,and the cost which incurred in logistics distribution is an important part of the total logistics cost,so the optimization of the distribution cost is the key to reducing the total cost of logistics.At the same time,for logistics companies,scientific distribution methods help companies achieve the goal of low operating costs and enable companies to gain competitive advantages in fierce market competition.Company Y is a third-party logistics company,based on the background of company Y,through the field research in Company Y and the analysis of existing distribution plans,it is found that there are some problems in the distribution process of company Y,such as the dispersion of customers caused by improper product storage,the low loading rate of vehicles,the unreasonable handling of pick-up orders,the transportation distance is too long due to unreasonable route arrangement,and the unreasonable way of splitting orders.Focusing on the distribution problem of company Y,comprehensively considering the fixed cost and fuel consumption cost of the vehicle during the distribution process,under the condition of multiple distribution centers,the optimization model of split delivery vehicle routing problem with pickup and delivery is established,and an algorithm is designed to solve this model.The algorithm solution steps are mainly divided into four stages: customer allocation,order splitting,vehicle routing solution,and pick-up optimization scheme design.Firstly,the customers are clustered and assigned to the appropriate depot by the clustering algorithm,and the multi-depot vehicle routing problem is decomposed into two single depot vehicle routing problems.Secondly,appropriate order splitting rules and methods is designed to split customer orders to improve vehicle loading rate.Thirdly,because the vehicle routing problem is an NP-hard problem,when facing a large-scale example,the exact algorithm cannot get the exact solution in a short time,and a multi-population genetic algorithm is selected to solve the vehicle routing problem,and the chromosome structure of the algorithm is designed according to the problem studied.Finally,for the optimized of pickup order,with the help of the idea of Nearest Insertion Algorithm,the optimization of the pick-up process is completed.The algorithm designed above is used to optimize the actual order of company Y on a certain day,and the distribution plans before and after optimization are compared to analyze the superiority and feasibility of the algorithm.After optimization,company Y effectively reduce the number of distribution routes,the transportation cost and fixed cost are significantly reduced,the total cost is saved,and the average loading rate of vehicles is also significantly improved.Through this research,the distribution plan of company Y 's household appliances project is improved,operating costs are reduced,and more profitable is bringing to company Y.