Abstract
Recent research has shown that optimal picker tours in rectangular warehouses exhibit deterministic travel patterns within each aisle, and that certain previously considered traversals are unnecessary. Using these insights, this paper proposes modifications to dynamic programming algorithms that improve computational efficiency without affecting optimality. For layouts with and without a central cross-aisle, the modifications preserve linear-time complexity in the number of aisles while reducing the number of state-action evaluations per stage. The proposed modifications reduce computational effort by factors up to 1.81, confirmed by numerical experiments. These findings are encouraging and highlight how structural refinements can yield significant improvements in practical performance of algorithms.
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