Managing congestion in supply chains via dynamic freight routing: An application in the biomass supply chain

This paper manages congestion in the supply chain via dynamic freight routing and using multi-modal facilities in different time periods of a year. The proposed mixed integer non-linear program (MINLP) model captures the trade-offs that exists between investment, transportation, and congestion management decisions. A linear approximation of the proposed MINLP model is then solved using a hybrid Benders-based rolling horizon algorithm. The performance of the algorithm is tested on a case study that uses data from the Southeast USA biomass supply chain network. Extensive numerical experiments provide managerial insights to manage congestion from the biomass supply chain network.