Classification code assignment for a parcel distribution network. (June 2020)

• Record Type: Journal Article
• Authors: Park, Jaesang; Kim, Byung-In
• Is Part Of: Computers & industrial engineering. Volume 144(2020)
• Publication Date: 2020-06
• Subjects: Transportation -- Large-scale hub-and-spoke network -- Capacitated multiple allocation problem -- Code assignment -- Parcel courier; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106447
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A real-world hub-and-spoke allocation problem and its mathematical model are presented. The parcel classification system currently used by a courier company is introduced. Assigning each group of destination spokes a unique code is a critical issue. The proposed algorithm provides a good solution in a reasonable amount of time. Abstract: We consider the capacitated hub-and-spoke network of a parcel courier company that consists of multiple hubs and hundreds of spokes. Parcels are collected at origin spokes, sent to hubs, sorted and consolidated on the basis of their destination spokes, and then sent to their destination spokes. Importantly, it is required that all parcels be classified based on their destination spokes at the origin spokes because the hub to which each parcel is sent is based on the connection between the hubs and its destination. As there are hundreds of destinations, the classification task at the origin spokes is very labor intensive. To solve this problem, courier companies employ a classification code system, which significantly reduces the number of categories that need to be classified by making a limited number of destination spoke groups and assigning a classification code to each group. We propose a mathematical programming model and algorithm for the assignment of classification codes to the spokes and generation of a corresponding network flow design. Experimental results from benchmark datasets generated based on real-world hub-and-spoke networks demonstrate the efficiency of our proposed algorithm.