Integrated storage space allocation and ship scheduling problem in bulk cargo terminals

This study is motivated by the practices of large iron and steel companies that have steady and heavy demands for bulk raw materials, such as iron ore, coal, limestone, etc. These materials are usually transported to a bulk cargo terminal by ships (or to a station by trains). Once unloaded, they are moved to and stored in a bulk material stockyard, waiting for retrieval for use in production. Efficient storage space allocation and ship scheduling are critical to achieving high space utilization, low material loss, and low transportation costs. In this article, we study the integrated storage space allocation and ship scheduling problem 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 is developed and then solved using a 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

Storage space allocation problem at inland bulk material stockyard

© 2020 Elsevier Ltd We consider the storage space allocation problem at an inland bulk stockyard, which aims to find an effective way to store the shapeless materials. Due to the specific storage and handling means in the stockyard, unloading, stacking and reclaiming operations need to be scheduled in an integrated manner. Viewing the space of each stock pad in the yard as a series of unit slots, we first develop a novel MIP formulation which can avoid generating scattered small fields. We then decompose the model by exploiting the relationships among the above operations, and develop a logic-based Benders approach to solve it optimally