Two-echelon logistics delivery and pickup network optimization based on integrated cooperation and transportation fleet sharing. (15th December 2018)

• Record Type: Journal Article
• Authors: Wang, Yong; Peng, Shouguo; Xu, Chengcheng; Assogba, Kevin; Wang, Haizhong; Xu, Maozeng; Wang, Yinhai
• Is Part Of: Expert systems with applications. Volume 113(2018)
• Page Start: 44
• Page End: 65
• Publication Date: 2018-12-15
• Subjects: Two-echelon logistics delivery and pickup network -- IPSO–ACO hybrid algorithm -- Transportation fleet sharing -- Cooperative alliance -- Strictly monotonic path; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2018.06.037
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlights: Vertical and horizontal synergies are combined to optimize logistics networks. Customer and fleet sharing is considered to minimize total operating costs. An IPSO–ACO hybrid algorithm is applied to reallocate customers to facilities. Shapley value model is improved to properly distribute collective profits. Optimal adhesion sequences are determined for both grand and two sub-alliances. Abstract: The optimization of the two-echelon logistics delivery and pickup network (2E-LDPN) is a strategical and tactical task which can efficiently be achieved by establishing cooperative alliances. Under the coordination of logistics services providers or logistics facilities of the existing network, high operating costs caused by cross and long distance transportation can be reduced via the inclusive reorganization of the entire network. In order to minimize the total cost, this study simultaneously considers semitrailer truck and vehicle sharing, and establishes a linear mathematical model capable of interpreting real world practices under single or multiple alliances scenarios. An Improved Particle Swarm Optimization (IPSO) algorithm and the Ant Colony Optimization (ACO) algorithm are reasonably combined into a hybrid meta-heuristics to solve the cooperative 2E-LDPN optimization problem. This algorithm combines the merits of IPSO and ACO with local and global search capabilities, and redistributes customer zones on the basis of region partitioning solutions in order to rationalize transportation activities. Finally, an Improved Shapley value model is applied to guarantee profits allocation's fairness and is proved reliable in term of alliance stability. Empirical results out of a case study in Chongqing city show that the IPSO–ACO hybrid algorithm is superior to three well-known algorithms on the cost solution and the number of iterations. Using the Improved Shapley value model and strictly monotonic path (SMP) selection principles, optimal adhesion sequences for two alliances and a grand alliance are yielded. The implemented transition from two sub-alliances based network to the grand alliance is in line with real-world's practices and provides decision makers with a useful tool for the design of cooperative alliances. In addition, the proposed cooperation strategy and profit allocation method enable companies to increase cost savings and the logistics network's efficiency. Besides, semitrailer truck and vehicle sharing as feature of collaboration conditional clauses reduces the size of transportation fleets, and promotes greener logistics operations.