Optimization Of Vehicle Routing Problem And Trip Distribution Of Company L

In recent years,with the in-depth integration of advanced information technology and logistics activities such as mobile internet,big data,cloud computing,China's logistics has been developed rapidly.However,the proportion of China's logistics costs in GDP is still relatively high,and there is a certain gap with developed countries.In the components of logistics costs,transportation costs account for more than 50%.It plays an important role in logistics costs.Reducing transportation costs is an important method for promoting economic structural reform and high-quality development.It also helps logistics companies to reduce total costs and increase efficiency,transform the industry,and improve corporate competitiveness and customer satisfaction.L company is a third-party logistics company which mainly provides business distribution services for two brands.After investigation and research,the company mainly has the following problems in distribution:(1)The route arrangement is unreasonable,and the distribution distance is too long.(2)There are some problems of unreasonable loading,wasted capacity and overload.(3)There is an imbalance between the driving time of vehicles and the working hours of drivers.(4)Working hours are too long and the problem of overtime is serious.(5)The process of urgent orders is unreasonable.Aiming at the actual problems of the L company,a mathematical model of the vehicle routing problem which minimizing total distribution distance and a mathematical model of trip allocation which minimizing total distribution costs and optimizing the vehicle traveling time and a mathematical model of urgent order optimization are established respectively.Because vehicle routing problem is an NP-hard problem,exact algorithm cannot get the exact solution of a large-scale example in a short time.In order to improve the calculation efficiency,a heuristic algorithm is used.The Metropolis sampling criterion in simulated annealing algorithm is adopted,which improving local optimization ability.After improving the stages of chromosome selection,crossover,and evolutionary reversal,an improved hybrid genetic simulated annealing algorithm is formed.Because trip allocation is a multi-objective optimization problem,the non-dominated sorting genetic algorithm is designed and used.Aiming at the urgent order distribution,the routes are planned by using the method of Saving Algorithm.Finally,optimize according to the actual data of L company on a certain day,the distribution plans before and after optimization are compared and analyzed to verifying the feasibility of algorithm.