Hierarchical allocation-routing heuristic algorithm for crowd-shipping problem with time windows, transshipment nodes, and delivery options

• Published in: Expert systems with applications Vol. 268; p. 126325
• Main Authors: Thao Nguyen, Nguyen Ngoc, Hop, Nguyen Van
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 05.04.2025
• Subjects: Alternative Delivery Points; Crowd Shipping; Transshipment Nodes; Variable Neighborhood Search; Alternative Delivery Points; Crowd Shipping; Variable Neighborhood Search; Transshipment Nodes
• ISSN: 0957-4174
• DOI: 10.1016/j.eswa.2024.126325

The study addresses the Crowd Shipping Problem with Time Windows, Transshipment Nodes, and Delivery Options (CSPTW-TN-DO) in last-mile delivery for e-commerce. A novel hierarchical heuristic algorithm is developed to classify customers by appropriate vehicle types, allocate online orders to specific occasional vehicles, and generate an efficient routing plan for each vehicle. The K-means clustering method and the proposed hierarchical assignment procedures classify and allocate online/offline customers to pickup points, transshipment notes, and alternative delivery points for the appropriate dedicated or occasional vehicles. Then, the Variable Neighborhood Search algorithm provides an efficient routing solution for each vehicle. Experimental results show that the proposed hierarchical allocation-routing heuristic algorithm outperforms the existing Adaptive Large Neighborhood Search (ALNS) method in terms of total distribution costs.