Publication Type
Journal Article
Version
acceptedVersion
Publication Date
6-2017
Abstract
We consider a single-item continuous-review (r, q) inventory system with a renewal demand process and independent, identically distributed stochastic lead times. Using a stationary marked-point process technique and a heavy-traffic limit, we prove a previous conjecture that inventory position and inventory on-order are asymptotically independent. We also establish closed-form expressions for the optimal policy parameters and system cost in heavy-traffic limit, the first of their kind, to our knowledge. These expressions sharpen our understanding of the key determinants of the optimal policy and their quantitative and qualitative impacts. For example, the results demonstrate that the well-known square-root relationship between the optimal order quantity and demand rate under a sequential processing environment is replaced by the cube root under a stochastic parallel processing environment. We further extend the study to periodic-review (S, T) systems with constant lead times.
Keywords
inventory system, (r, q) policy, stochastic leadtime, asymptotic analysis, heavy traffic limit.
Discipline
Operations and Supply Chain Management
Research Areas
Operations Management
Publication
Operations Research
Volume
65
Issue
5
First Page
1414
Last Page
1428
ISSN
0030-364X
Identifier
10.1287/opre.2017.1623
Publisher
INFORMS
Embargo Period
6-11-2018
Citation
ANG, Marcus; SIGMAN, Karl; SONG, Jing-Sheng; and ZHANG, Hanqin.
Closed-form approximations for optimal (r, q) and (S, T) policies in a parallel processing environment. (2017). Operations Research. 65, (5), 1414-1428.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/5831
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1287/opre.2017.1623