2018/01/26 by Abdulkader S. Hanbazazah, Hanbazazah, Abdulkader S, Luis E. Abril +5
Engineering · #FOS: Mathematics #Maritime Ports and Logistics #Optimization and Control (math.OC) #Urban and Freight Transport Logistics #Vehicle Routing Optimization Methods
paper · pdf · doi:10.48550/arxiv.1801.08921
openalex publication_date 2018/01/26 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
The growth in online shopping and third party logistics has caused a revival\nof interest in finding optimal solutions to the large scale in-transit freight\nconsolidation problem. Given the shipment date, size, origin, destination, and\ndue dates of multiple shipments distributed over space and time, the problem\nrequires determining when to consolidate some of these shipments into one\nshipment at an intermediate consolidation point so as to minimize shipping\ncosts while satisfying the due date constraints. In this paper, we develop a\nmixed-integer programming formulation for a multi-period freight consolidation\nproblem that involves multiple products, suppliers, and potential consolidation\npoints. Benders decomposition is then used to replace a large number of integer\nfreight-consolidation variables by a small number of continuous variables that\nreduces the size of the problem without impacting optimality. Our results show\nthat Benders decomposition provides a significant scale-up in the performance\nof the solver. We demonstrate our approach using a large-scale case with more\nthan 27.5 million variables and 9.2 million constraints.\n