A Novel Decomposition Method for Two-stage Stochastic Port Management Problem

Abstract

Inland waterway transportation network significantly supports the overall freight transportation of the nation. In order to ensure efficient and timely commodity transportation through this network, this study aims at developing a reliable inland waterway transportation network considering the interactions between different transportation entities along with considering the uncertain commodity supply and un-predictable waterway conditions over time. A capacitated, multi-commodity, multi-period, stochastic, two-stage mixed-integer linear programming (MILP) model is pro-posed to capture this stochastic, time variant behavior of the water-depth along any link of the inland waterway under consideration. Additionally, we proposed a parallelized hybrid decomposition algorithm to solve the real-life test instances of this com-plex NP-hard problem. The proposed algorithm is capable of producing high quality solutions within a reasonable amount of time. Further, a case study is demonstrated for the Southeast region of the United States and a number of managerial insights are drawn that magnifies the impact of different key input parameters on the overall inland waterway transportation network under consideration.