Research On Optimization Of Vehicle Distribution Problem Based On Heuristic Algorithm

Vehicle routing problem is one of the classical combinatorial optimization problems,and it is widely used in social development.With the rapid development of e-commerce,the timeliness of material distribution is required more highly.With the continuous expansion of the scale of the problem,the traditional optimization algorithm is getting worse in ability of the vehicle routing problem of logistics distribution,so it is very difficult to find the optimal solution of the problem.It is important for many scholars to design an effective algorithm or to improve present algorithms for optimization problems.In order to reduce the transportation cost of a kind of vehicle routing problem in the process of vehicle delivery and improve the satisfaction of customers,a problem model is established based on the case of conceited takeout distribution in the delivery industry.The goal of the problem is to reduce the total distance and total delay time of delivery service so as to minimize the total cost.Therefore,a hybrid genetic algorithm is designed to solve the vehicle routing problem of multi-vehicle delivery.From the benchmark test sample att[48],22 customers were randomly selected as the experimental example to verify the algorithm.By comparing the results of two classical algorithms(e.g.First Come First Service,FCFS and Nearest Neighbor,NN),the designed hybrid genetic algorithm has good performance in solving problem.On the basis of studying the above distribution problem,to reduce total delay time caused by dynamic interference and reduce distance in the process of the distribution further,a strategy to solve the take-out delivery vehicle routing problem in uncertain environment is designed based on the receding horizon control(RHC)framework.The nearest neighbor(NN)algorithm is used to schedule customers of current window.The resultant algorithm is called RHC-NN.The basic idea is that gathering the orders in a period and dividing them into multiple windows according to the expected delivery time.NN is used to search the location of the order,a single vehicle is used in the distribution service,and set out from and return to the distribution center for many times.Under a variety of constraints,the orders with dynamic interference are selected by the receding horizon control strategy with the maximum extent,and they are put into the corresponding service time window.In each window,the service paths of the distribution for the orders of the customers are optimized in real time so that to the orders can be distributed reasonably.Finally,the test example used in the third chapter is set as basic test data.Under the condition of crowded,normal,non-crowded,high-frequency disturbance and low-frequency disturbance,the results of three algorithms are compared.The experimental results show that the proposed RHC-NN can meet the needs of merchants and customers under the five dynamic conditions,such as the crowded,normal,non-crowded,high-frequency disturbance and low-frequency disturbance.RHC-NN can not onlysignificantly reduce the total delay time of distribution service,but also shorten the total distance of takeout distribution,save the penalty cost of late arrival or early arrival.Therefore,the economic benefit of independent management of merchants is increased.