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| Main Authors: | , , , |
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| Format: | Artículo Open Access |
| Published: |
Wiley
2025
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| Subjects: | |
| Online Access: | https://onlinelibrary.wiley.com/doi/10.1002/nav.70013 |
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Table of Contents:
- Adjustable Target‐Oriented Robust Optimization for Inventory Management Daoheng Zhang Guopeng Song Roel Leus Lianmin Zhang Naval Research Logistics (NRL) ABSTRACT We present an adjustable target‐oriented robust optimization (ATRO) framework tailored for inventory managers aiming to meet a specified cost target. We assume that demand is uncertain and characterized by an uncertainty set lacking complete structural information. While the center of the set is known as the nominal value of the demand, the size of the set is not prescribed. The objective of the ATRO framework is to maximize the size of the uncertainty set within given cost target constraints. Expanding upon the existing target‐oriented robust decision‐making framework, we explore two ATRO models that utilize static and linear decision rules, respectively. This exploration is designed to assess the influence of different decision rules on achieving predetermined cost targets. Theoretical analysis indicates that ATRO models utilizing linear decision rules can achieve lower worst‐case inventory costs while accommodating larger uncertainty sets compared to their static counterparts. Numerical experiments underscore the efficiency of ATRO in managing inventory, especially when dealing with cases of large demand variability. 10.1002/nav.70013 http://onlinelibrary.wiley.com/termsAndConditions#vor