Enhancing Urban Logistics Efficiency: A Mixed Heuristic Approach for Solving the Two-Echelon Location-Routing Problem with Recommended Satellites

The Two-Echelon Location-Routing Problem with Recommended Satellites (2E-LRPRS) presents a critical optimization challenge in last-mile delivery systems. We propose a hybrid heuristic framework combining greedy satellite selection with Nearest Neighbor routing for second-echelon distribution. This approach minimizes total transportation costs while achieving significant computational efficiency. Experimental results demonstrate a 4.29% average improvement in solution quality for small-to-midsized instances compared to existing methods. The greedy component identifies high-impact satellite locations, while TSP-based routing optimizes paths between satellites and customers. Our model balances solution quality with computational requirements, making it particularly suitable for dense urban logistics. Operational flexibility is enhanced through support for ad hoc driver participation and decentralized vehicle deployment, ensuring adaptability in dynamic urban environments.