Comparison of mixed-integer linear programming models for delivery problem with transshipments and battery swapping

Abstract

Efficient last-mile delivery in urban areas is challenged by cost, congestion, and environmental impact. We presented two Mixed-Integer Linear Programming (MILP) formulations for the multi-depot and multi-robot vehicle routing problem with transshipment and battery swapping, further enhanced with a partitioning orbitope symmetry-breaking method. Comparing these models confirmed the partitioning orbitope approach significantly improved runtimes for large-scale instances compared to standard methods.

Mohammad Fili

Postdoctoral Research Fellow

My research interests include Healthcare Data Analytics, Machine Learning, and Optimization.