In a recent paper, Fisher et al. (2001) present a method tomitigate end-effects in lot sizing by including a valuation term for end-of-horizon inventory in the objective function of the short-horizon model. Computational tests show that the proposed method outperforms the Wagner-Whitin algorithm and the Silver-Meal heuristic, under several demand patterns, within a rolling horizon framework. We replicate the computational tests also including a straightforward method that assumes the same knowledge about future demand as the ending inventory valuation method. Our results indicate that the superior performance reported by Fisher et al. is to a large extent due to the fact that their method assumes that quite accurate knowledge about future demand is available, whereas the traditional methods do not use any information about demand beyond the short model horizon. Moreover, when quite accurate knowledge about future demand is indeed available, our results suggest that for some demand patterns, ending inventory valuation is not the most effective way to use this knowledge. Furthermore, we point out a minor mistake in the results reported by Fisher et al.
End Effects Dynamic Lot Sizing Ending Inventory Valuation