Optimal Dynamic Lot-Sizing In A Reverse Logistics Environment With Unlimited Purchased Returns
We deal with the dynamic lot-sizing problem (DLSP) in a setting where a large amount of returned items can be acquired in each period at costs and fully remanufactured to meet a deterministic but time-varying demand of a single product over a finite planning horizon. We propose a model that considerstime-varyingseparate set-up and inventory holding costs for the manufactured and remanufactured items, time-varying separate variable manufacturing and remanufacturing processing costs, and time-varying acquisition and inventory holding costs for the returned items.We develop an extension of the Wagner-Whitin algorithmin order to solve the problem optimally. Because of the generality of the cost structure we consider, our proposed procedure can be readily used as a "stand-alone," or as the foundation for solution procedures aimed at more realistic models involving multiple-items and capacity limits.
Index Terms - Lot-sizing, reverse logistics, production planning, dynamic programming