The Continuous-Time Joint Replenishment Problem: <i>ϵ</i>-Optimal Policies via Pairwise Alignment

The main contribution of this paper resides in developing a new algorithmic approach for addressing the continuous-time joint replenishment problem, termed [Formula: see text]-pairwise alignment. The latter mechanism, through which we synchronize multiple economic order quantity models, allows us to devise a purely combinatorial algorithm for efficiently approximating optimal policies within any degree of accuracy. As a result, our work constitutes the first quantitative improvement over power-of-2 policies, which have been state-of-the-art in this context since the mid-1980s. Moreover, in light of recent intractability results, by proposing an efficient polynomial-time approximation scheme for the joint replenishment problem, we resolve the long-standing open question regarding the computational complexity of this classical setting. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Israel Science Foundation [Grant 1407/20].

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Publication Details

Journal
Management Science
Published
2024-08-30
DOI
https://doi.org/10.1287/mnsc.2023.00705
Citations
4
Primary Topic
Supply Chain and Inventory Management
Type
article
Field-Weighted Citation Impact
2.11
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article

The Continuous-Time Joint Replenishment Problem: ϵ-Optimal Policies via Pairwise Alignment

Danny Segev
4 citations
Management Science
Supply Chain and Inventory Management
2.11
article

The Continuous-Time Joint Replenishment Problem: ϵ-Optimal Policies via Pairwise Alignment

Danny Segev
article en
4 citations

Abstract

The main contribution of this paper resides in developing a new algorithmic approach for addressing the continuous-time joint replenishment problem, termed [Formula: see text]-pairwise alignment. The latter mechanism, through which we synchronize multiple economic order quantity models, allows us to devise a purely combinatorial algorithm for efficiently approximating optimal policies within any degree of accuracy. As a result, our work constitutes the first quantitative improvement over power-of-2 policies, which have been state-of-the-art in this context since the mid-1980s. Moreover, in light of recent intractability results, by proposing an efficient polynomial-time approximation scheme for the joint replenishment problem, we resolve the long-standing open question regarding the computational complexity of this classical setting. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Israel Science Foundation [Grant 1407/20].

Management ScienceVol. 71(5)
Tel Aviv University (IL)
Partnerships for the goals
Openalex Percentile: Top 10%
Supply Chain and Inventory Management
2.11
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