Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems

We consider a centralized two-level distribution system that consists of one warehouse and multiple retailers. The retailers are non-identical and face independent Poisson demand. The system adopts a fixed-interval order-up-to policy, in which the warehouse and retailers each order in a fixed interv...

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Main Authors: Wang, Qinan, Wan, Guangyu
Other Authors: Nanyang Business School
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/172526
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1725262023-12-12T07:43:12Z Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems Wang, Qinan Wan, Guangyu Nanyang Business School Business::Operations management Myopic Optimal Allocation Virtual Allocation We consider a centralized two-level distribution system that consists of one warehouse and multiple retailers. The retailers are non-identical and face independent Poisson demand. The system adopts a fixed-interval order-up-to policy, in which the warehouse and retailers each order in a fixed interval to raise the echelon inventory position to a fixed base stock level. Shortages in the system are fully backlogged but transshipments between retailers are not allowed. The fixed-interval order-up-to policy has been studied in the literature under virtual allocation that reserves a unit of warehouse stock immediately after a unit of demand occurs. We consider an inventory control system that is different in two aspects. First, the warehouse implements myopic optimal allocation that allocates stock to retailers only at points of delivery to minimize system cost. Second, the warehouse adopts a non-stationary base stock policy to order stock for retailers according to their replenishment schedules. We develop methods to exactly evaluate and fully optimize this inventory control system. In a numerical study, we demonstrate that myopic optimal allocation reduces system cost by an average of 5.89% with a range from 1.45% to 10.13% as compared to virtual allocation. In addition, we develop an iterative procedure to alleviate the problem of dimensionality for myopic optimal warehouse stock allocation and a close-to-optimal heuristic solution that can significantly reduce computation. This work was supported by the National Natural Science Foundation of China (72274055); the Natural Science Foundation of Hunan Province (2022JJ30176). 2023-12-12T07:43:12Z 2023-12-12T07:43:12Z 2023 Journal Article Wang, Q. & Wan, G. (2023). Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems. European Journal of Operational Research, 309(3), 1112-1124. https://dx.doi.org/10.1016/j.ejor.2023.02.025 0377-2217 https://hdl.handle.net/10356/172526 10.1016/j.ejor.2023.02.025 2-s2.0-85150020543 3 309 1112 1124 en European Journal of Operational Research © 2023 Elsevier B.V. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Business::Operations management
Myopic Optimal Allocation
Virtual Allocation
spellingShingle Business::Operations management
Myopic Optimal Allocation
Virtual Allocation
Wang, Qinan
Wan, Guangyu
Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
description We consider a centralized two-level distribution system that consists of one warehouse and multiple retailers. The retailers are non-identical and face independent Poisson demand. The system adopts a fixed-interval order-up-to policy, in which the warehouse and retailers each order in a fixed interval to raise the echelon inventory position to a fixed base stock level. Shortages in the system are fully backlogged but transshipments between retailers are not allowed. The fixed-interval order-up-to policy has been studied in the literature under virtual allocation that reserves a unit of warehouse stock immediately after a unit of demand occurs. We consider an inventory control system that is different in two aspects. First, the warehouse implements myopic optimal allocation that allocates stock to retailers only at points of delivery to minimize system cost. Second, the warehouse adopts a non-stationary base stock policy to order stock for retailers according to their replenishment schedules. We develop methods to exactly evaluate and fully optimize this inventory control system. In a numerical study, we demonstrate that myopic optimal allocation reduces system cost by an average of 5.89% with a range from 1.45% to 10.13% as compared to virtual allocation. In addition, we develop an iterative procedure to alleviate the problem of dimensionality for myopic optimal warehouse stock allocation and a close-to-optimal heuristic solution that can significantly reduce computation.
author2 Nanyang Business School
author_facet Nanyang Business School
Wang, Qinan
Wan, Guangyu
format Article
author Wang, Qinan
Wan, Guangyu
author_sort Wang, Qinan
title Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
title_short Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
title_full Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
title_fullStr Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
title_full_unstemmed Fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
title_sort fixed-interval order-up-to policies and myopic optimal warehouse stock allocation for one-warehouse multiple-retailer systems
publishDate 2023
url https://hdl.handle.net/10356/172526
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