A two-echelon location routing problem with mobile satellites for last-mile delivery: mathematical formulation and...

Area of Science:

• Operations Research
• Logistics and Supply Chain Management

Background:

• Traditional last-mile delivery relies on costly fixed satellite warehouses to manage traffic uncertainties.
• The two-echelon location routing problem (2E-LRP) models these systems but incurs high implementation and operational expenses.

Purpose of the Study:

• To propose a novel two-echelon location routing problem with mobile satellites (2E-LRP-MS) to reduce delivery costs.
• To introduce a heuristic algorithm, clustering-based simultaneous neighborhood search (CSNS), for solving the 2E-LRP-MS.

Main Methods:

• Developed the 2E-LRP-MS by replacing fixed satellites with mobile first-echelon vehicles (CT) that replenish second-echelon vehicles (CF) en-route.
• Employed consolidation points (CP) for temporary parking, reducing reliance on expensive fixed satellite infrastructure.
• Designed the CSNS heuristic incorporating probabilistic mechanisms, k-means clustering for facility selection, and simultaneous neighborhood search with local optimization.

Main Results:

• Demonstrated the significant cost-saving flexibility of the 2E-LRP-MS model compared to traditional 2E-LRP.
• Validated the superior searching efficiency of the CSNS heuristic over existing methods and the CPLEX solver for two-echelon routing problems.

Conclusions:

• The 2E-LRP-MS offers a more cost-effective and flexible approach to last-mile delivery logistics.
• The CSNS heuristic provides an efficient and effective solution for the complex 2E-LRP-MS, outperforming current benchmarks.