Robust optimization approaches in inventory management: Part B—the comparative study

Abstract

This comparative study, constituting Part B of our extensive investigation into Robust Optimization (RO) in inventory management, builds on the foundational insights from Part A’s survey. It conducts a thorough analysis of various RO formulations and algorithms, emphasizing their practical application, efficacy, and computational considerations in inventory management contexts. This study is meticulously structured to address the pivotal inquiries identified in Part A, encompassing the effective representation of uncertainty, the selection of optimal decision criteria, the influence of decision rules on inventory management performance, computational challenges, and the adaptability of these methods to evolving technological and market conditions. This research juxtaposes theoretical findings with empirical data, offering a comprehensive evaluation of the strengths, limitations, and practical implications of each robust inventory model discussed in the literature. This investigation not only complements the survey in Part A but also serves as a standalone, in-depth contribution to robust inventory management.