Abstract
Based on the real-world inventory control problem of a capacitated healthcare apparel service centre in Hong Kong which provides tailor-made apparel-making services for the elderly and disabled people, this paper studies a partial backordered continuous review inventory control problem in which the product demand follows a Poisson process with a constant lead time. The system is controlled by an (Q,r) inventory policy which incorporate the stockout risk, storage capacity, and partial backlog. The healthcare apparel service centre, under the capacity constraint, aims to minimize the inventory cost and achieving a low stockout risk. To address this challenge, an optimization problem is constructed. A real case-based data analysis is conducted, and the result shows that the expected total cost on an order cycle is reduced substantially at around 20% with our proposed optimal inventory control policy. An extensive sensitivity analysis is conducted to generate additional insights.
Highlights
This paper reports an analytical study which is based on a real case of a healthcare apparel service centre, called the Troels H
As the centre is nonprofit-making, having an efficient and sustainable operation [1] means the centre has to minimize the cost. Concerning such a situation, we study in this paper a single item partially backordered inventory system governed by a continuous review (Q,r) policy: (i) when the inventory position reaches the reorder point r, an order is placed with the batch size Q; (ii) the storage space is capacitated, and unmet demands are partially backordered; and (iii) there is a “free waiting time” during which there is no backorder cost for the model
Based on the real-world operations of a healthcare apparel service centre in Hong Kong, this paper explores a partialbackorder (Q,r) inventory control policy with capacity and service level constraints
Summary
This paper reports an analytical study which is based on a real case of a healthcare apparel service centre, called the Troels H. To make the situation more challenging, in addition to the target stockout risk consideration, in the healthcare apparel centre’s inventory control problem, there is a capacity constraint. Journal of Healthcare Engineering but not least, facing the stockout risk, some of the demands are lost while some are backlogged because some customers are willing to wait but not all This situation is known as “partial backlog” in inventory control, and it affects the design of the optimal inventory (Q,r) policy significantly. The conventional (Q,r) policies which do not consider stockout risk, capacity, and partial backlog together will fail to be optimal and cannot be used to solve the inventory control problem faced by the healthcare apparel service centre mentioned above. Based on the healthcare apparel service centre’s inventory control challenges, this paper aims to develop a novel optimal (Q,r) policy which can incorporate the stockout risk, storage capacity, and partial backlog into the optimization model.
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