Inventory Control Under Stochastic Lead Time and Stochastic Demand
Inventory Control Under Stochastic Lead Time and Stochastic Demand

Author: Kenneth R Rand (Jr)

Publisher:

Published: 1965

Total Pages: 109

ISBN-13:

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An attempt is made to investigate the behavior of an inventory system in which lead time, the size of the demand order, and the time between successive demand orders are all random variables with known probability distributions. Since adequate analytical mathematical models are not existant, a computer-based simulation model is used to study the inventory system. An introduction to the inventory problem and a description of inventory systems currently in use are provided. The formulation of the model is described. Results are presented as graphs of stockout time as a function of reorder point.

Demand Forecasting and Inventory Control
Demand Forecasting and Inventory Control

Author: Colin David Lewis

Publisher: Routledge

Published: 1997

Total Pages: 172

ISBN-13: 1855732416

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A practical guide to the forecasting and inventory control methods used in commercial, retail and manufacturing companies. Colin Lewis explains the theory and practice of demand forecasting methods, the links between forecasts produced as a result of analyzing demand data and the various methods by which this information, together with cost information on stocked items, is used to establish the controlling parameters of the most commonly-used inventory control systems.

Inventory Management with Stochastic Lead Times
Inventory Management with Stochastic Lead Times

Author: Kumar Muthuraman

Publisher:

Published: 2013

Total Pages: 34

ISBN-13:

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This article analyzes a continuous time back-ordered inventory system with stochastic demand and stochastic delivery lags for placed orders. This problem in general has an infinite dimensional state space and is hence intractable. We first obtain the set of minimal conditions for reducing such a system's state space to one-dimension and show how this reduction is done. Next, by modeling demand as a diffusion process, we reformulate the inventory control problem as an impulse control problem. We simplify the impulse control problem to a Quasi-Variation Inequality (QVI). Based on the QVI formulation, we obtain the optimality of the (s, S) policy and the limiting distribution of the inventory level. We also obtain the long run average cost of such an inventory system. Finally, we provide a method to solve the QVI formulation. Using a set of computational experiments, we show that significant losses are incurred in approximating a stochastic lead time system with a fixed lead time system, thereby highlighting the need for such stochastic lead time models. We also provide insights into the dependence of this value loss on various problem parameters.