An advanced solution for efficient logistics management at both company and network level

This paper proposes an advanced solution for efficient logistics management in urban areas based on a unified scheme able to address both static and dynamic decision making at a company and network level. The proposed solution generates the most efficient urban distribution plan utilizing an evolutionary metaheuristic approach and a backpressure framework that provide competitive scheduling and routing decisions. An empirical study based on real data is conducted assessing the performance of the proposed advanced solution and the reported results of the evaluation experiments demonstrate its generality and robustness.