The discrete forward–reserve problem – Allocating space, selecting products, and area sizing in forward order picking

Dynamic warehouse optimization using predictive analytics.

“…In the following section, we review the methodology of Walter et al (2013) to solve the discrete forward-reserve problem. Then, we propose a greedy heuristic solution procedure for solving the discrete forward-reserve problem.…”

“…The optimal size of forward area is also investigated through the proposed algorithms. Walter et al (2013) Problem.) In this type of knapsack problem, the items are categorized into k classes, and exactly one item must be taken from each class.…”

“…We now elaborate on a test instance generation for DAA problem with respect to Walter et al (2013)'s tests. The three changing parameters in instances are as below:…”

“…Prioritizing to solve any of these three problems and then using the resulting solution as the input to others is not the best strategy. A heuristic for the discrete forward-reserve problem has been suggested (Walter et al, 2013), but it is not applicable for large problems due to the solution time. They also assume that the slots are always wider than the SKUs and do not solve the three mentioned problems together.…”

“…One deficiency of the greedy heuristic is that it provides no posterior bound on the performance of the solution (Hackman and Platzman, 1990). Walter et al (2013) relax the assumption of continuous space forward area and solve the discrete assignment, allocation, and sizing of the fast picking area. However, they do not solve these three problems simultaneously.…”