Optimization For The Internal And External Scheduling Problem With Cross-docking Considering The Value Of Distribution Services

The cross-docking distribution network has the characteristics of high operational efficiency and low storage.And it has significant advantages in saving distribution time and reducing logistics costs.The operation of cross-docking involves facilities selection,pick-up,delivery,and internal unloading,sorting integration,loading,etc.The key to its implementation lies in the effective coordination of internal and external scheduling.At present,the research on internal scheduling or external scheduling is relatively deep,while the integration research is quite rare.At the same time,enterprises pay more attentions to customer service in actual logistics.Therefore,this paper optimizes the internal and external scheduling problem with cross-docking considering the value of distribution services,which has strong theoretical and practical significance.The main research work of this paper is as follows:(1)In terms of optimization objects,this paper considers the integrated management of cross-docking and customer's different perception for service time:(1)Taking the external and internal scheduling decisions,including facility selection,routing,dock door assignment and vehicle sequencing as research objects.(2)Combined with the customer fuzzy time window,introducing the prospect theory and constructing the distribution service value function.(2)The construction and solving model of two-stage optimization for internal and external scheduling problem with cross-docking.First,considering the need of integrated management of cross-docking,a two-stage optimization model of cross-docking is established,based on the correlation between internal and external scheduling.Secondly,according to the characteristics of the model,a two-stage tabu search algorithm is designed to solve the problem.Finally,the simulation verifies that the model and algorithm are feasible and effective.(3)The construction and solving model of integrated optimization for internal and external scheduling problem with cross-docking.First,in order to improve the overall benefit of the cross-docking distribution network,a bi-objective integration optimization model of cross-docking is established,taking the total cost of distribution and scheduling efficiency as the optimization goal.Secondly,because the mismatches between internal and external scheduling can easily occur in the solution process,a special correction operation is presented.Combined with Pareto optimization theory,a multi-objective tabu search algorithm with special correction is designed.Finally,the simulation results show that:(1)The external scheduling has great influence on the optimization of internal scheduling,so integrated optimization has practical significance.(2)The model can take both internal and external scheduling into account,and is suitable for enterprises that pay attention to overall benefits.(3)The proposed algorithm has a good correction effect.(4)The construction and solving model of integrated optimization for internal and external scheduling problem with cross-docking considering the value of distribution services.First,in order to balance the level of distribution service,taking the value of distribution service as one of the optimization objectives,and then a triple-objective integration optimization model of cross-docking is established.Secondly,due to the weakness of multi-objective optimization search,the gray target analysis is used to guide the algorithm search.And then a multi-target tabu search algorithm based on gray target analysis is proposed.Finally,the simulation results show that:(1)There is a certain correlation between total cost,scheduling efficiency and the value of distribution services,and it is impossible to achieve the best at the same time.The model can take all of them into account and provide more feasible solutions for decision makers.(2)The multi-objective algorithm based on gray target analysis can get a better Pareto frontier.