Optimization Study Of Collaborative Two-echelon Multi-depot Multi-period Logistics Network Based On Resource Sharing Modes

The rapid development of urban intelligent logistics puts forward new and higher requirements for the increasing customer demands and service characteristics,as well as the rational allocation and maximum utilization of logistics resources,and then makes the system optimization of urban logistics network face new severe challenges.Collaboration and resources sharing between the logistics enterprises can improve customer service quality to a certain extent and improve the efficiency of cargo transport,but the existing researches on collaboration and resources sharing seldom refer to in logistics customer service in the network of periodic feature extraction,rational configuration of system resources and customer service problems such as the division of time interval.Therefore,the research on the system collaboration and resource sharing of multiple facilities in the urban logistics network during multiple service periods needs to be further expanded.Based on this,this paper mainly studies the following aspects:(1)Collaborative multi-depot multi-period pickup and delivery network optimization problem.In order to meet customers’ periodic service requirements and realize effective coordination between pickup and delivery services,this paper studies a mixed open-closed vehicle path optimization problem for sharing customers,service facilities and transportation resources between pickup and delivery centers.Firstly,a multi-objective optimization model is constructed,which includes minimizing logistics operational cost,service waiting time and the number of vehicles.Then,a hybrid optimization algorithm based on K-means clustering and improved multi-objective particle swarm optimization(IMOPSO)was proposed to solve the model,and a population selection mechanism based on grid method and crowding distance was introduced to improve the local and global search ability of the hybrid algorithm,so as to quickly obtain Pareto optimization solutions.Finally,combining with the third-party logistics enterprise conducts a practical analysis of data,the results show that the multidepot pickup and delivery network with resource sharing and rationalization of open and closed path configuration,can effectively reduce the total logistics operational cost,the number of vehicles and the service waiting time.(2)Collaborative two-echelon multi-depot multi-period delivery network optimization problem.In order to realize service synchronization and optimal resource configuration in the two-echelon logistics network,this paper studies a delivery network optimization problem in which logistics facilities form a coalition alliance in the firstechelon logistics network to achieve reasonable vehicle scheduling in the second-echelon logistics network.Firstly,a two-echelon logistics network model is established to optimize the delivery path in multiple centers and the shared path in multiple periods.Then,put forward a hybrid heuristic method based on three-dimensional customer clustering and non-dominated sorting genetic algorithm(NSGA-III)for the model,and designs a kind of elite iterative process,including genetic operation of selection,crossover,mutation and an optimal selection mechanism based on reference point,so as to ensure the diversity of the multi-objective optimization solution;Finally,by comparing the data set with other optimization algorithms,the effectiveness and applicability of the hybrid optimization algorithm proposed in this paper for solving the path optimization of collaborative networks are analyzed and verified.In addition,the results of optimization network show that the strategy of resource sharing and synchronization based on multidepot and multi-period collaborative network can improve the operation efficiency and reasonable resource configuration of logistics network.(3)Collaborative alliance optimization of multi-depot and multi-period logistics network.Firstly,several profit distribution methods are introduced,and profit distribution schemes of each alliance are obtained based on the cost saving of collaborative network.Secondly,the cost reduction percentage of each member in the alliance is calculated,and multiple alliances are analyzed and compared through strict monotone path(SMP)and diagonal rule to determine the optimal alliance.Then,a "snowball" theory is used to calculate the distance between the profit distribution scheme to the core center of the network revenue,so as to ensure the stability of the collaborative alliance.Finally,analyze the different types of collaboration forms in the single-echelon and two-echelon collaborative network,and through the comparison of multi-objective optimization network results and cost reduction percentage of alliance members,the optimal types of cooperation network can be obtained,to realize the reasonable configuration of logistics resources and the sustainable development of the collaborative logistics network.