Private Optimal Inventory Policy Learning for Feature-based Newsvendor with Unknown Demand

arXiv:2404.15466v1 Announce Type: cross
Abstract: The data-driven newsvendor problem with features has recently emerged as a significant area of research, driven by the proliferation of data across various sectors such as retail, supply chains, e-commerce, and healthcare. Given the sensitive nature of customer or organizational data often used in feature-based analysis, it is crucial to ensure individual privacy to uphold trust and confidence. Despite its importance, privacy preservation in the context of inventory planning remains unexplored. A key challenge is …

abstract arxiv commerce cs.lg customer data data-driven demand e-commerce feature features healthcare inventory nature organizational data policy research retail stat.ml supply chains type