research-article

The continuous delayed distribution problem

Authors:

Assaf AvrahamiAuthors Info & Claims

Volume 148, Issue C

https://doi.org/10.1016/j.cor.2022.105976

Published: 01 December 2022 Publication History

Abstract

Nowadays, decision makers (DMs) at companies have access to extensive and accurate data, which means they have the opportunity to grow and improve if they use the latent potential effectively. We address the complex problem of optimizing decisions in a multi-period one-warehouse multi-retailer inventory system with stochastic continuous demand and an option of delayed distributions. At the beginning of each period, the DM determines each retailer’s target stock levels, as well as the number of items to be held back at a central location for later distribution(s). Such a policy offers partial inventory pooling through the holdback quantity. The decisions in each period are data-driven, i.e., made based on sales data available through an information system up to that point in time.

We model the problem as a multi-stage stochastic program with recourse. For the general case, we develop a new recursive solution algorithm, which is based on subgradient optimization and an analysis of system dynamics. For the special case of two identical retailers and two periods, we provide explicit optimality conditions based on the subgradients. Using a large numerical study, we evaluate the performance of our proposed policy and compare it to two benchmark policies. We also demonstrate the impact of various problem parameters on the optimal solution and objective value.

Highlights

•

Model the continuous delayed distribution problem as multistage stochastic program.

•

Analytical solution for special two-by-two case.

•

Develop algorithms to solve the problem and evaluate their performance.

•

Evaluate and benchmark model & algorithms, investigate impact of problem parameters.

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Index Terms

The continuous delayed distribution problem
1. Information systems

Index terms have been assigned to the content through auto-classification.

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cover image Computers and Operations Research

Computers and Operations Research Volume 148, Issue C

Dec 2022

466 pages

ISSN:0305-0548

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Elsevier Science Ltd.

United Kingdom

Publication History

Published: 01 December 2022

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