Research And Application Of Logistics Vehicle Route Planning Based On Improved Genetic Algorithm

With the rapid development of e-commerce platform in China,the logistics industry is booming.At present,the transportation process is located in the core position of the logistics,which accounts for a large proportion of cost.The general problem of transportation for logistics enterprises is that the planning of vehicle path mainly depends on the subjective experience of the driver,which directly affects the transportation efficiency,transportation cost and customer satisfaction.In view of the above problems,this paper realizes the rational planning of vehicle path through hybrid genetic algorithm.The specific research include:(1)Study and analyze the related theory of vehicle routing problem,and mainly focus on the vehicle routing problemwith time window,and research and analysis show that the genetic algorithm has strong global search characteristics when solving the vehicle routing problem with time windows(VRPTW).The simulation annealing algorithm has strong local search ability when solving VRPTW.Therefore,this work combines the genetic algorithm and simulated annealing algorithm to search for a better global solution.(2)In order to further improve the quality of the solution,the initial population is generated by the chaos algorithm.At the same time,the improved proportion selection method and elite reservation strategy are used to select the individual.Then the improved adaptive probability is applied to the optimization of the crossover operator and mutation operator.Finally,the individuals are further optimized by simulated annealing algorithm.(3)The model of vehicle routing problem with time window is set up.The model takes the sum of the fixed cost,transportation cost and the time window penalty cost as the objective function,and seeks the minimum value of the target function by taking the soft time window and the vehicle load weight as the main constraint conditions.(4)The hybrid genetic algorithm is implemented by MATLAB,and the example of Solomon data set is selected to testing the algorithm.The distribution route plan will be compared with the best published results.The minimum number of vehicles and the shortest mileage will be very close to the known optimal solution.In addition,By comparing the hybrid genetic algorithm with the basic genetic algorithm and simulated annealing algorithm,the results shows that hybrid genetic algorithm can effectively reduce the total logistics cost,and fully verify the effectiveness,reliability and generality of the hybrid genetic algorithm to solve the vehicle routing with time window.The vehicle routing problem with time window studied in this paper has very important practical significance for logistics enterprises,which can arrange the vehicle route reasonably,reduce the transportation cost,improve the distribution efficiency and enhance the customer satisfaction.