Strategic Inventory Placement in Large-Scale Multi-Echelon Networks
Author | : Josef Svoboda |
Publisher | : |
Total Pages | : 0 |
Release | : 2022 |
ISBN-10 | : OCLC:1375165736 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Strategic Inventory Placement in Large-Scale Multi-Echelon Networks written by Josef Svoboda and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The placement and sizing of safety stocks in supply chains pose a challenging optimization problem. State-of-the-art multi-echelon inventory optimization models, such as the guaranteed-service approach, are non-linear and depend on statistical, time-series-based approaches that require distributional and parametric assumptions. We propose a data-driven, non-parametric and distribution-free approach for safety stock planning in multi-echelon inventory networks that utilizes historical demand and feature data. We extend data-driven optimization in inventory control from newsvendor models to multi-period and multi-echelon problems. Our model accommodates general, acyclic multi-echelon networks and simultaneously determines safety stock allocation and sizing by setting cost-optimal base stocks for all stages under consideration of service requirements. By developing a mixed-integer programming formulation and a Benders decomposition method, we offer a novel methodological approach to a well-studied problem that can be solved with commercial mathematical programming solvers. We also provide a probabilistic analysis of the data-driven performance relative to an oracle solution when sample data is limited. We show that the mixed integer programming approach is scalable by solving 38 large-scale supply chain benchmark networks with assembly, distribution, and general structures.