Inventory Management for Supply Chains with Uncertainty

@mastersthesis{li2023,
  title = {Inventory Management for Supply Chains with Uncertainty},
  author = {LI, KANGYE},
  year = {2023},
  month = aug,
  publisher = {Lehigh University},
  keywords = {Industrial engineering--},
  abstract = {Inventory management is a challenging task due to the presence of uncertainty, such asdemand uncertainty and supply uncertainty. It is necessary for companies to achieve a balance between meeting customer demand and minimizing holding costs. This dissertation explores the impact of uncertainty on supply chain systems, and presents simple heuristics to optimize inventory order up-to-levels, enabling efficient management of the system. In our first topic, we consider a single-stage system with demand uncertainty and a minimum order quantity (MOQ) requirement. Given the challenges associated with implementing complex optimal ordering policies in practice, we propose some easily implementable heuristic ordering policies based on well-known base-stock or (s, S) policies. We propose algorithms to determine optimal ordering parameters in the heuristic ordering policies, and test the performance of our heuristics by numerical experiments. Additionally, a sensitivity analysis is conducted to assess the influence of the MOQ requirement on the system. In our second topic, we study a periodic-review, one-warehouse multiple-retailer (OWMR) inventory system with both demand uncertainty and supply disruptions. We assume that each stage follows a base-stock policy and that the allocation policy is first-come, first-served (FCFS). We provide an explicit cost function using a �top-down� approach and optimize the system by the projection method. We also propose two heuristics for this problem. One heuristic combines a heuristic for serial systems subject to supply disruptions with the decomposition-aggregation (DA) heuristic for distribution systems without disruptions. The other heuristic combines DA and the newsvendor problem with disruptions. In the last topic of this dissertation, we consider a distribution system with demand uncertainty and supply disruptions, which is an extension of the research conducted in the second topic. We derive the cost function of the system by analyzing the inventory dynamics. In addition, we propose three heuristics to achieve near-optimal base-stock levels. Two of these heuristics are modified versions derived from the heuristics discussed in the previous chapter, while the third heuristic is a hybrid that combines the first two heuristics.},
}