Economic Warehouse Lot Scheduling: Approximation Schemes via Efficiently-Representable DP-Encoded Policies
Danny Segev

TL;DR
This paper introduces a polynomial-time approximation scheme for the economic warehouse lot scheduling problem, enabling near-optimal dynamic replenishment policies for multiple commodities with efficient policy representations.
Contribution
It develops novel analytical tools and algorithms to construct efficiently-representable, near-optimal dynamic policies, advancing the computational understanding of this classic inventory problem.
Findings
Established a polynomial-time approximation scheme for multiple commodities.
Provided efficient representations for near-optimal dynamic policies.
Achieved progress on the fundamental open question of policy complexity.
Abstract
In this focused technical paper, we present long-awaited algorithmic advances toward the efficient construction of near-optimal replenishment policies for a true inventory management classic, the economic warehouse lot scheduling problem. While this paradigm has accumulated a massive body of surrounding literature since its inception in the late '50s, we are still very much in the dark as far as basic computational questions are concerned, perhaps due to the intrinsic complexity of dynamic policies in this context. The latter feature forced earlier attempts to either study highly-structured classes of policies or to forgo provably-good performance guarantees altogether; to this day, rigorously analyzable results have been few and far between. The current paper develops novel analytical foundations for directly competing against dynamic policies. Combined with further algorithmic…
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Taxonomy
TopicsSupply Chain and Inventory Management · Scheduling and Optimization Algorithms · Auction Theory and Applications
