Optimizing inland waterway port management decisions considering water level fluctuations

Abstract

This study presents a multi-commodity, multi-period mixed-integer linear programming model to efficiently manage the inland waterway port operations while minimizing the overall supply chain cost. An accelerated Benders decomposition algorithm is developed to solve this challenging NP-hard problem. Proposed algorithm can produce high-quality solutions consistently within a reasonable amount of time. Numerical results show that considering water level fluctuations the test region is required to use an additional 81.5% barges and 39.7% towboats. Further, managerial insights are drawn for different key input parameters that impact port operations.