Dynamic Last-Mile Logistics Optimization with Mobile Micro- Warehouses: A Multi-Period Model Based on Parcel Lockers

Abstract

This research focuses on optimizing last-mile logistics in urban areas using mobile microwarehouses and parcel lockers. A dynamic multi-period mathematical model was developed to minimize transportation costs and reduce traffic congestion. The model was solved using two separate approaches: exact resolution with CPLEX, and metaheuristic optimization using Simulated Annealing (SA) and Grey Wolf Optimizer (GWO). The goal was to compare their efficiency and performance. Python was used for modeling and experimentation. The results revealed that each method offers specific advantages in terms of solution quality and computation time, providing valuable insights for sustainable urban logistics planning.