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.
