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Title: Production planning and inventory control of two-product recovery system in reverse logistics
Authors: PAN JIE
Keywords: Inventory Control, Recovery System, Reverse Logistics, Approximate Dynamic Programming, Periodic Review, Threshold Level Policy
Issue Date: 12-May-2010
Source: PAN JIE (2010-05-12). Production planning and inventory control of two-product recovery system in reverse logistics. ScholarBank@NUS Repository.
Abstract: This research focuses on a two-product recovery system in the field of Reverse Logistics. As far as the knowledge about current literature, this research could be regarded as the first study on the multi-product recovery system involving two products and two flows of returned items. Firstly, dynamic programming has been used to model the system in a finite horizon. Secondly, the optimal threshold level policy has been obtained for the system in a single period. For the single-period problem, the usual approach is to use Karush-Kuhn-Tucker (KKT) conditions to find the optimal solution. In this case, the answer is very complex which results in 21 different cases. However, after analyzing these 21 cases, we found out that they can be represented by an optimal multi-level threshold policy. This optimal policy is characterized by 6 order-up-to levels and 3 switching levels. Even though this multi-level threshold policy might not be optimal for the multi-period problem, it is intuitive, easy to use and provides good managerial perspectives. Hence, we apply this policy to the multi-period problem in the situation of lost sales at first. We have found that different from the single-period problem, the threshold will not only depend on the current-period cost parameters, but also on the future cost-to-go function. Thirdly, we have developed an efficient way to compute these threshold levels. Unlike the usual approach which uses a single function (or piecewise function) to represent the cost-to-go function, we just need to estimate the gradient of the cost-to-go function at the points of interest. These gradients will be used to compute the threshold level. Hence, the performance of the results will not depend on the function we assume which can be a challenge for most of the approximate dynamic programming approaches. In addition, we develop an Infinitesimal Perturbation Analysis (IPA) based approach to estimate the gradient. This approach not only uses the least computing resources but also its estimation quality is better. The results of the numerical experiments show that the performance of this threshold policy is found to be promising under a wide range of settings. Finally, we have extended the multi-period problem to the situation of backorder. Furthermore, the lead time effect is investigated based on a simple case, where production lead time and recovery lead time of each product are assumed to be equal to the same nonzero constant. This multi-level threshold policy also shows good performance under a wide range of settings.
Appears in Collections:Ph.D Theses (Open)

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