Mixed multi-echelon location routing problem with differentiated intermediate depots. (March 2023)

• Record Type: Journal Article
• Authors: Chen, Yunkai; Zhao, Quanwu; Wang, Wei; Zhang, Shu
• Is Part Of: Computers & industrial engineering. Volume 177(2023)
• Publication Date: 2023-03
• Subjects: Mixed multi-echelon -- Location routing problem -- Differentiated intermediate depots -- Iterated local search -- Path relinking; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2023.109026
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A mixed logistics network which is better than two-echelon logistics network. Designing an efficient algorithm to solve the MME-LRP. Giving suggestions for express companies to redesign their logistics network. Abstract: With the increasing of E-commerce parcels in China in recent years, the logistics networks of many express companies are more and more unreasonable. Considering the distribution of parcels is regionally related, we describe a mixed multi-echelon (MME) urban logistics network to handle the regionally distributed parcels. The MME network contains limited urban distribution centers (UDCs), many differentiated intermediate depots (IDs), and a large number of terminals. This research constructs a mixed integer linear programming (MILP) to solve the mixed multi-echelon location routing problem (MME-LRP) where the location and the type of IDs are determined. A hybrid heuristic algorithm based on iterated local search and intensified by path relinking (HH-ILS-PR) is proposed to tackle the problem. The quality of our algorithm and the practicability of the MME network are verified by three sets of instances: two of them are adapted from benchmark instances of 2E-LRP and one is developed from real-world data. In the real-world instance, MME urban logistics network reduces the cost by 11.08% compared with two-echelon urban logistics network. We also present several managerial implications to express companies.