Advancements in Inventory Management: Insights From INFORMS Franz Edelman Award Finalists
回顾了1985至2023年Franz Edelman奖决赛入围者在库存管理中应用运筹学和管理科学的方法，包括仿真优化、深度学习、动态定价等，展示了这些技术如何优化库存、降低成本并提升客户满意度。
This article provides a comprehensive overview of the advancements and applications of operations research (OR) and management science (MS) in inventory management described by the Franz Edelman Award finalists from 1985 to 2023. The research presents the transformative potential of OR/MS in addressing complex inventory management challenges across various industries. Through an in-depth examination of the methodologies and solutions employed by these studies, we highlight the strategic implementations of several OR/MS techniques, including simulation-optimization, deep learning and advanced forecasting, dynamic pricing and yield management, and stochastic modeling. The analysis reveals the tangible benefits realized, such as optimized inventory levels, reduced costs, improved profits and revenue, and improved customer satisfaction. This research underscores the critical role of inventory process optimization and risk mitigation in navigating uncertainties and demand fluctuations. The managerial insights derived from these initiatives provide a roadmap for practitioners seeking to implement advanced OR/MS methodologies in real-world inventory management. The findings also encourage the adoption of innovative methods to enhance the operational efficiency and competitiveness. Through this exploration, we aim to stimulate further innovation and research in the evolving field of inventory management and to celebrate the achievements in applied analytics brought forth by the Franz Edelman Award finalists.