Stockyard storage space allocation in large iron ore terminals

Abstract

Due to the increasing large demand of iron ore, large iron ore terminals are becoming critical nodes in the international shipping network. As the buffer area for temporary storage of iron ore, stockyards of iron ore terminals often emerge as the bottlenecks in the entire transportation process. Traditional experience-based operation strategy for iron ore terminals is insufficient to handle mega-size terminals and more complicated operations, such as ore-mixing. As compared to container terminals, relatively little attention has been paid to the stockyard space management of dry bulk terminals. It is of great necessity to improve the stockyard operations of iron ore terminals via operations research and optimization techniques. In this paper, we investigate the stockyard storage space allocation problem arising from large iron ore terminals with particular consideration of the ore-mixing operations. We propose a flexible and accurate modeling approach for the storage space of the iron ore terminal stockyard, and develop a mixed integer linear programming model with the objective of minimizing total travel distance of all the incoming iron ores. A heuristic approach based on genetic algorithm is designed to obtain near-optimal solutions in an efficient way. Computational experiments based on real-world iron ore terminals are conducted, and the results show satisfactory performance of the heuristic algorithm both in efficiency and effectiveness.