Optimization of Multimodal Cargo Transportation Using Column Generation

Abstract

With global freight transportation expanding substantially, freight transportation ought to surmount amplified costs and emissions associated with long distances through multimodal transportation (MT). Similarly, promulgating the necessity for ecological solutions calls for transport modes apart from road. Hence, MT permits the incorporation of several modes to employ their distinct advantages. To capture these advantages, a cost-minimization optimization model was developed to address the routing and scheduling of orders. The model is used to identify the schedule of optimal services using column generation (CG), where the sub-problem is a k-shortest path problem. Finally, the model's performance and efficacy were tested using a real-case study. The application also highlighted the relationship between the order parameters and services characteristics on total costs, including penalty and emission costs.

Date of Award	Jul 2022
Original language	American English