The Reserrch On Logistics Scheduling Algorithm Based On Electronic Commerce

Enterprises have paid attention to logistics which as a part of enterprises' "third profit source".Vehicle routing problem is a hot issue in the field of logistics management.Because of its complexity and diversity,it is a very challenging problem to reasonably arrange the vehicle and their driving path at the lowest cost.Many scholars have studied the vehicle routing problem,since it is proposed in 1959.With the development of electronic commerce,logistics has become more and more important in the enterprise.This paper mainly studies the vehicle routing problem that make a research from an electronic commerce enterprises.This paper firstly studies the general model of vehicle routing problem,then the vehicle routing problem in electronic commerce is analyzed and propose a problem which is called "Multi-multi Pickup and Delivery Vehicle Routing Problem with Time Windows based on Satisfaction".This paper mainly studies the vehicle routing problem in two aspects:static vehicle scheduling and dynamic vehicle scheduling.Then,we analyze the static state of MMPDVRPTWS,that is,all the customer demand is known and the path information is not changed in the distribution process.In this paper,the two phase method is used to solve the problem,and the customer is grouped according to the customer's demand and location information with an insertion heuristic algorithm,and then a hybrid genetic algorithm is used to optimize the path.Through the study of genetic algorithm,it is found that the operation of genetic algorithm is easy to fall into local convergence due to its inherent characteristics,which lead to the emergence of local optimal solution.In this paper,a local search algorithm is used as the mutation operator of genetic algorithm,which can prevent the local optimal solution.In the end,the paper discusses the setting of the target weight value in fitness function,and then compares the results with the conventional genetic algorithm.The results show that the hybrid genetic algorithm has some advantages in solving the problem.Finally,we analyze the dynamic state of MMPDVRPTWS,that is,the path information and the customer request can be changed during the distribution process.In this paper,the customer demand in a "working day"is simulated,and a "working day" is divided into several "time slices".We make the requirement which is created during one "time slices" insert to the path and hybrid genetic algorithm is used to optimize the path.At last,the dynamic scheduling strategy is verified by experiments.