Towards low-carbon e-commerce return logistics : optimization for simultaneous pickup and delivery

Abstract

Purpose: The rapid expansion of e-commerce platforms has made collaborative logistics networks essential. This study tackles the intricate challenge of optimizing pickup and delivery activities in constrained areas, striving to meet the ever-increasing e-commerce demands while maintaining tight control over distribution costs. Design/methodology/approach: This study develops a vehicle routing problem with simultaneous pickup and delivery with time windows (VRPSPDTW) model and validates it using simulated annealing (SA) and a hybrid algorithm combining simulated annealing with tabu search (SA-TS). Random pickup and delivery requests are generated following a uniform distribution to evaluate the model’s performance. Findings: This research validates the VRPSPDTW model and the SA and SA-TS algorithms, demonstrating their superior flexibility and comprehensiveness compared to traditional methods. The findings demonstrate their effectiveness in managing dynamic demands, optimizing first-mile and last-mile coordination, and improving efficiency in collaborative e-commerce logistics. Research limitations/implications: To validate the model, this study employed simplified demand patterns and a uniform distribution. Future research could integrate a broader range of constraints and test scalability across various logistics scenarios to enhance practical applicability. Practical implications: The proposed VRPSPDTW model optimizes pickup and delivery routes in e-commerce logistics centers, enhancing network coordination, reducing operational costs and improving delivery efficiency, demonstrating significant practical value. Originality/value: This research provides an innovative solution for collaborative logistics networks. By addressing first-mile pickups and last-mile deliveries with the VRPSPDTW model and heuristic algorithms, the study fosters operational efficiency and demonstrates practical approaches to dynamic challenges in e-commerce logistics.