Asymptotically Optimal Lagrangian Policies for Multi-Warehouse Multi-Store Systems with Lost Sales

Operations Research

45 Pages Posted: 6 Apr 2020 Last revised: 25 Apr 2021

See all articles by Sentao Miao

Sentao Miao

University of Colorado Boulder

Stefanus Jasin

University of Michigan, Stephen M. Ross School of Business

Xiuli Chao

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Date Written: March 11, 2020

Abstract

We consider a periodic-review inventory control problem for the Multi-Warehouse Multi-Store system with lost sales. We focus on a time horizon during which the system receives no external replenishment. Specifically, each warehouse has a finite initial inventory at the beginning of the horizon, which is then periodically allocated to the stores in each period in order to minimize the total expected lost-sales costs, holding costs, and shipping costs. This is a hard problem and the structure of its optimal policy is extremely complex. We develop simple heuristics based on Lagrangian relaxation that are easy to compute and implement, and have provably near-optimal performances. In particular, we show that the losses of our heuristics are sublinear in both the length of the time horizon and the number of stores. This improves the performance of existing heuristics in the literature whose losses are only sublinear in the number of stores. Numerical study shows that the heuristic performs very well. We also extend our analysis to the setting of positive delivery lead times.

Suggested Citation

Miao, Sentao and Jasin, Stefanus and Chao, Xiuli, Asymptotically Optimal Lagrangian Policies for Multi-Warehouse Multi-Store Systems with Lost Sales (March 11, 2020). Operations Research, Available at SSRN: https://ssrn.com/abstract=3552995 or http://dx.doi.org/10.2139/ssrn.3552995

Sentao Miao (Contact Author)

University of Colorado Boulder ( email )

256 UCB
Boulder, CO CO 80300-0256
United States

Stefanus Jasin

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Ann Arbor, MI MI 48109
United States

Xiuli Chao

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

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