Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo del Vendedor de Periódicos× | Modelos de stock de seguridad y punto de pedido× | |
|---|---|---|
| Campo | Investigación operativa | Investigación operativa |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1951 | 1998 |
| Autor original≠ | Arrow, Harris & Marschak | Silver, Pyke & Peterson |
| Tipo≠ | Stochastic single-period inventory optimization | Stochastic inventory control model |
| Fuente seminal≠ | Arrow, K. J., Harris, T., & Marschak, J. (1951). Optimal inventory policy. Econometrica, 19(3), 250–272. DOI ↗ | 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 | Newsboy Model, Single-Period Inventory Model, Christmas Tree Problem, Gazete Satıcısı Modeli | Buffer Stock, Reserve Stock, Reorder-Point Model, Emniyet Stoğu |
| Relacionados | 3 | 3 |
| Resumen≠ | The Newsvendor Model is a single-period stochastic inventory optimization framework that determines the profit-maximizing order quantity when demand is uncertain and unsold units cannot be carried forward. Formally introduced by Arrow, Harris, and Marschak (1951) in their foundational work on optimal inventory policy, the model balances the cost of ordering too much (overage) against the cost of ordering too little (underage) to yield a closed-form optimality condition known as the critical ratio. | 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. |
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