Previous block stacking research focused on determining the depth of a storage row to store a single product under dedicated storage and random storage conditions to minimize the sum of the cost of storage and the cost of storing and retrieving the product. The single-product block stacking problem has been treated for the cases of single and multiple depths of storage rows. However, we are not aware of a multi-product formulation of the block stacking problem having been studied previously. Here, we explore the use of dynamic programming to determine the optimum row depths for storing and retrieving unit loads of multiple products under random storage and dedicated storage conditions. Due to the size of the state space that exists when multiple products are considered, heuristic procedures are explored and the results are compared with the optimum solution obtained.
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