Application And Research Of Urban Logistics Vehicle Routing Problem Based On Evolutionary Algorithm

As the "accelerator" of modern national economic development and the "third profit source" of enterprise income,logistics industry plays an important role in improving the national economy of developing countries,promoting the reform of industrial structure and improving the international competitiveness of the world.In China,reducing the logistics transportation cost by 1% will correspondingly increase the direct economic benefits by more than 400 billion yuan.Therefore,improving the logistics management level and reducing the logistics cost are the top priorities in the current logistics work.The key to reduce the logistics cost is to shorten the transportation distance,so it is of great practical significance to build an effective distribution model with limited resources and find the best vehicle distribution scheme with the shortest distribution distance.Evolutionary algorithm plays an important role in vehicle path optimization.Compared with the traditional algorithm,it has the advantages of large scale,short time and good effect.Firstly,this paper studies the domestic and foreign literatures on vehicle path problem and analyzes the research bottleneck of VRP problem.Secondly,on the basis of VRP standard model,corresponding constraints are added to build CVRP and multi-logistics company collaborative distribution model,so as to make it more in line with the actual distribution problem.Then,a simulated annealing algorithm based on golden sine was proposed,and CVRP model was used to verify the search competitive advantage of the improved SA algorithm.Then,an ant-lion optimization algorithm combining levitical flight and golden sine is proposed,and the search accuracy advantage of the improved ant-lion optimization algorithm is verified with 12 standard functions,which provides a research idea for the optimization of simulated annealing algorithm.Finally,the new ant lion optimization algorithm and simulated annealing algorithm is designed in the new classic LGSALO-SA hybrid optimization algorithms,forecast accuracy as VRP standard examples of analysis,proves that the hybrid algorithm is extremely strong search competitiveness,and apply it to the three logistics enterprise collaborative logistics distribution model of the distribution of actual case,verify the feasibility of LGSALO-SA algorithm and optimization ability.Research results show that the improved ant lion optimization algorithm and simulated annealing hybrid optimization algorithm has a good search competitiveness,also shows that the logistics vehicle routing problem with evolutionary algorithm combining,compared with the traditional ways to solve the plan quickly out of the optimal distribution route,effectively reduce the distribution range of motor vehicles and transport costs,for solution of the urban logistics vehicle routing problem has obvious advantages,is an effective method for reducing distribution costs.