Research On Optimization Technology For Vehicle Routing In Logistics Distribution

The logistics industry is the result of the deepening of modern socialized production and specialized division of labor.With the growth of China's economy and the rapid development of the service industry,the logistics industry not only affects the development of the society and the improvement of people's living standards,but also is one of the important indicators of the degree of modernization and international competitiveness of a country.As the core function of the logistics system,the quality of logistics distribution directly affects the logistics cost of the enterprise and the customer's satisfaction with the logistics service.Therefore,in the distribution functions,optimizing the vehicle's delivery route is essential impact on the entire logistics transport speed,cost,and efficiency.The Vehicle Routing Problem(VRP)is an NP and there are many constraints on the problem,especially introducing the two factors: the Time Windows and Multi-depot,which make the solution of the problem more difficult.Therefore,how to find the optimal solution quickly and efficiently becomes the focus of current research.This paper mainly focuses on three mainstream vehicle routing optimization problems: Capacitated Vehicle Routing Problem(CVRP),Vehicle Routing Problem with time windows(VRPTW),and Multiple Depot Vehicle Routing with Time Windows(MDVRPTW).The paper analyzes the status quo and development trend of the Vehicle Routing Problem,researches the solution to the Vehicle Routing Problem,and focuses on the research and improvement of Simulated Annealing and Ant Colony algorithm to solve the VRP.For the problem that the Simulated Annealing algorithm has low precision and long processing time,and the Ant Colony algorithm easily traps in local optimum.An improved simulated annealing algorithm and an improved ant colony algorithm are proposed.Improved temperature lowering way,parameter settings,and solution space in the Simulated Annealing algorithm and the Ant Colony algorithm selection probability,global pheromone update method,pheromone volatile factors,pheromone concentration update methods,and the settings of various parameters.The simulation analysis of the improved algorithm shows that: The improved algorithm not only has a great improvement in time and accuracy,but also the algorithm can converge quickly and effectively avoid the algorithm falling into local optimum.Proposing the Simulated Annealing-Ant Colony combined algorithm based on Ant Colony algorithm,which is applied to solve the problem of vehicle routing optimization in logistics distribution.In order to verify the feasibility,efficiency and accuracy of the combined algorithm,the literature analysis and the CVRP example on the VRP authoritative website were used as data sources for simulation analysis:the combination algorithm has high accuracy for CVRP calculations of different scales,and the time for searching the optimal result is also greatly improved.The improved combinatorial algorithm not only has a good capability of optimization,but also has better improvement in accuracy and run time than traditional methods.Then,The combined algorithm designed for VRPTW is used to simulate and analyze some test cases of Solomon design.The simulation results are compared with the data of VRP authoritative website.The optimal solutions that obtained by the combination algorithm is consistent with the authoritative website.Finally,The combination algorithm is used to analyze the case,and Designed a reasonable and optimal delivery plan for T company's logistics distribution.Researching on MDVRPTW in deep,and proposing an idea that combines the location optimization and the route optimization of the depot solves the MDVRPTW problem.Firstly,the distribution center location is optimized.Secondly,converting the MDVRPTW into multiple VRPTW by decomposition method and then the combined algorithm is used to solve each VRPTW.Finally,merging the solution of each VRPTW is the solution of MDVRPTW.Experimental simulation results show that the MDVRPTW solution result after optimization of the depot position is compared with the MDVRPTW solution result with the fixed position of the depot.After optimizing the distribution center position,the accuracy of the shortest delivery distance is increased by about 2.6% compared with non-optimizing.This paper researches the optimization method of VRP,An improved simulated annealing algorithm and an improved ant colony algorithm are proposed,and proposes Simulated Annealing-Ant Colony combined algorithm based on Ant Colony algorithm as the main body,which solves the problem of CVRP,VRPTW and MDVRPTW.According to experiment simulation,the combined algorithm has a great improvement in time and accuracy,and has a good application value in solving vehicle routing problem.