Integrated Storage Space Allocation and Ship Scheduling Problem in Bulk Cargo Terminals

This study is motivated by the practice of large iron and steel companies, which have steady and heavy demands for bulk raw materials such as iron ore, coal, limestone and so on. These materials are usually transported to a bulk cargo terminal by ships (or to a station by trains). Once discharged, they are moved to and stored in bulk material stock yard, waiting for retrieval for production use. Efficient storage space allocation and ship scheduling are critical to achieve high space utilization, low material loss and low transportation costs. In this paper, we study the integrated storage space allocation and ship scheduling problem (IASP) in the bulk cargo terminal. Our problem is different from other associated problems due to the special way that the materials are transported and stored. A novel mixed-integer programming model (MILP) is developed, and then solved by Benders decomposition algorithm, which is enhanced by the use of various valid inequalities, combinatorial Benders cuts, variable reduction tests and an iterative heuristic procedure. Computational results indicate that the proposed solution method is much more efficient than the standard solution software CPLEX.