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

Danny Segev ()
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Danny Segev: School of Mathematical Sciences and Coller School of Management, Tel Aviv University, Tel Aviv 69978, Israel

Management Science, 2025, vol. 71, issue 5, 4183-4197

Abstract: The main contribution of this paper resides in developing a new algorithmic approach for addressing the continuous-time joint replenishment problem, termed Ψ -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.

Keywords: inventory management; JRP; approximation scheme (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:71:y:2025:i:5:p:4183-4197

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