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Towards low-carbon e-commerce return logistics: optimization for simultaneous pickup and delivery
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DOI：10.1108/IMDS-01-2025-0026.png)
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Abstract
En 中文
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.
Keywords:
Heuristics
Collaborative logistics networks
E-commerce logistics
Sustainability
Return logistics
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