方法对比

	经济订货批量 (EOQ)	ABC分析：按年使用价值对库存进行分类	安全库存与订货点模型
领域	运筹学	运筹学	运筹学
方法族	Regression model	Process / pipeline	Regression model
起源年份	1913	1998	1998
提出者	Ford W. Harris	Pareto principle; Silver, Pyke & Peterson	Silver, Pyke & Peterson
类型	Deterministic inventory optimization model	Inventory segmentation technique	Stochastic inventory control model
开创性文献	Harris, F. W. (1913/1990). How many parts to make at once. Operations Research, 38(6), 947–950 (reprint).	Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd ed.). Wiley. ISBN: 978-0-471-11947-0	Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling (3rd ed.). Wiley. ISBN: 978-0-471-11947-0
别名	Wilson EOQ Model, Harris-Wilson Model, Optimal Lot Size Model, Ekonomik Sipariş Miktarı	Pareto Inventory Classification, 80-20 Inventory Rule, ABC Classification, ABC Stok Analizi	Buffer Stock, Reserve Stock, Reorder-Point Model, Emniyet Stoğu
相关	3	2	3
摘要	The Economic Order Quantity (EOQ) is a classic deterministic inventory model that identifies the order quantity minimizing the sum of annual ordering and holding costs. Introduced by Ford W. Harris in 1913 and later popularized by R. H. Wilson, EOQ assumes constant demand, fixed cost parameters, and instantaneous replenishment. It remains the foundational benchmark for inventory management in manufacturing, retail, and supply chain contexts where demand is relatively stable and costs are well-characterized.	ABC Analysis is a demand-value segmentation technique that divides inventory items into three classes — A, B, and C — based on their annual usage value (unit cost multiplied by annual demand). Rooted in the Pareto principle and codified for inventory management by Silver, Pyke, and Peterson (1998), it guides managers to concentrate control resources on the small fraction of items that drive the vast majority of total inventory spend.	Safety stock is an additional quantity of inventory held beyond expected demand during a replenishment lead time, designed to protect against stockouts caused by demand or supply uncertainty. Reorder-point models formalize this buffer by setting a trigger inventory level at which a new order is placed. Systematically developed within the stochastic inventory-control framework by Silver, Pyke, and Peterson (1998), the approach translates a desired customer-service level into a precise buffer quantity using the statistics of demand and lead-time variability.