Comparer des méthodes

	Analyse ABC : Classification des stocks par valeur d'usage annuelle	Quantité Économique de Commande (QEC)	Modèles de stock de sécurité et de point de commande
Domaine	Recherche opérationnelle	Recherche opérationnelle	Recherche opérationnelle
Famille	Process / pipeline	Regression model	Regression model
Année d'origine	1998	1913	1998
Auteur d'origine	Pareto principle; Silver, Pyke & Peterson	Ford W. Harris	Silver, Pyke & Peterson
Type	Inventory segmentation technique	Deterministic inventory optimization model	Stochastic inventory control model
Source fondatrice	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	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
Alias	Pareto Inventory Classification, 80-20 Inventory Rule, ABC Classification, ABC Stok Analizi	Wilson EOQ Model, Harris-Wilson Model, Optimal Lot Size Model, Ekonomik Sipariş Miktarı	Buffer Stock, Reserve Stock, Reorder-Point Model, Emniyet Stoğu
Apparentées	2	3	3
Résumé	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.	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.	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.