Abstract
Yard storage management involves tactical and operational decisions affecting bulk port productivity. The main challenge is to ensure that bulk materials are available and stored according to physical and managerial constraints while minimizing storage space utilization. This article studies a new variant of the storage location assignment problem by considering contamination constraints for bulk materials. The problem is inspired by a real case study of Africa's largest fertilizer hub port. To tackle the problem, a model-driven decision support system, optimizing the storage space while satisfying vessels' demands and avoiding contamination from overlapping bulk materials, is developed. A mixed-integer linear programming model is formulated, and an efficient rolling-horizon heuristic is investigated as a solution approach. Extensive numerical experiments are performed, and the results confirm the efficiency of this model-driven support system from both theoretical and practical points of view.
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