Inventory management model

In comparing drugs, a P T committee might use three different approaches inventory management, cost accounting, and clinical decision analysis [22]. The inventory management model assumes that all agents in a class are equivalent on safety, efficacy, and... 

See Park et al. (2006) tor a complex inventory management model for a single site. 

This model was recently employed in a periodic-review inventory management model by Aviv and Federgruen (2001). 

Lee, H., Pinto, J.M., Grossmann, I.E., and Park, S. (1996) Mixed-integer linear programming model for refinery short-term scheduling of crude oil unloading with inventory management Industrial el Engineering Chemistry Research, 35, 1630. 

This work presented a new model formulation that coordinates pipeline transportation with tank farm inventory management, including individual tanks details. The obtained model generates within the solution the rotation scheme for tanks that allows the verification of all required tank farm operations. 

The main achievement of the proposed model is to provide a detailed tank farm inventory management, looking into the sets of tanks of each product (rotation scheme). As future work it is proposed to improve the tanks cycle formulation and develop a set of examples to test the behavior of the Disaggregated Tanks Formulation. Additionally, it is proposed to develop a decomposition strategy to link subsequent time horizons. 

Almost all contributions to MIRSP use a time-continuous formulation and consider constant consumption and/or production rates for the products at the sites. One exception is Persson and Gothe-Lundgren (2005) using a time-discrete formulation. Moreover, production planning decisions are incorporated besides routing and inventory management. The second exception propose Christiansen et al. (2011) where a solution procedure for a MIRSP with time-varying consumption rates is described (but no mathematical model). 

This comprises e.g. inventory routing models for procurement via ship or pipeline (see Ronen (2002) or Moura et al. (2008)) and local tank management models (see e.g. Saharidis et al. (2009)). 

Christiansen, M. and Nygreen, B. Modelling path flows for a combined ship routingand inventory management problem. Annals of Operations Research, 82 391-413, 1998. 

As described in [18], the main challenges in the auto parts supply chain are (1) intermittent parts consumption with very low turns, (2) enormous disparity across part costs, (3) great variety across models, with hundreds and thousands of SKUs worth billions of dollars in inventory across the supply chain, (4) variable value of delivered service based on the severity of the failure, (5) lack of dealer interest in becoming efficient inventory managers and failure to see the connection between providing good service and selling cars. 

Erlenkotter D (1977) Capacity expansitm with imports and inventories. Manage Sci 23(7) 694—702 Freidenfelds J (1981) Capacity expansion analysis of simple models with applications. Elsevier North Holland, New York... 

Fixed reorder cycle inventory model—A form of independent demand management model in which an order is placed every n time units. The order quantity is variable and essentially replaces the items consumed during the current time period. Let M be the maximum inventory desired at any time, and let x be the quantity on hand at the... 

Fixed reorder quantity inventory model—A form of independent demand item management model in which an order for a fixed quantity, Q, is placed whenever stock on hand plus on order reaches a predetermined reorder level, R. The fixed order quantity Q may be determined by the economic order quantity, by a fixed order quantity (such as a carton or a truckload), or by another model yielding a fixed result. The reorder point R, may be deterministic or stochastic, and in either instance is large enough to cover the maximum expected demand during the replenishment lead time. Fixed reorder quantity models assume the existence of some form of a perpetual inventory record or some form of physical tracking, e.g., a two-bin system, that is able to determine when the reorder point is reached. These reorder systems are sometimes called fixed order quantity systems, lot-size systems, or order point-order quantity systems. 

Now consider the GT version of the newsvendor problem with two retailers competing on product availability. Parlar (1988) was the first to analyze this problem, which is also one of the first articles modeling inventory management in a GT framework. It is useful to consider only the two-player version of this game because then graphical analysis and interpretations are feasible. Denote the two players by subscripts i and j, their strategies (in this case stocking quantities) by Qi, Qj and their payoffs by tt. ... 

S. Kachani and G. Perakis. A fluid model of dynamic pricing and inventory management for make-to-stock manufacturing systems. Working Paper, MIT, 2002. 

Common Approaches for Modeling Demand Uncertainty and Forecast Evolution in the Inventory Management Literature... 

Sometimes, even when one has the reason to believe that a product experiences a demand that is stationary with independent realizations, one is still uncertain about the exact parametric specification of the demand distribution. A stream of inventory management research that considers the case in which certain parameters of the demand distributions are unknown, started with the papers Dvoretzky et al. (1952), Scarf (1959,1960) and Iglehart (1964). Azoury (1985) is cited very often in this context, and the following model follows closely the presentation there with slight changes of notation Suppose that the demands Dt are continuously distributed, with a probability density function that has a known statistical form, but with an unknown parameter (or vector of parameters) w. Specifically, let [Pg.404]

In this section we briefly describe a linear state space model that serves as a building block for the main models of collaborative forecasting processes we present in this chapter. We then present a well-known forecasting technique associated with this model namely, the Kalman filter. Let Xt be a finite, n-dimensional vector process called the state of the system. In the context of inventory management, this vector may consist of early indicators of future demand in the channel, actual demand realizations at various points of the channel, and so forth. Suppose that the state vector evolves according to ... 

In the previous section we presented a set of models of demand/forecast evolution that are fairly common in the inventory management literature. Clearly, this collection of models was not intended to be exhaustive. Nevertheless, these models share an important advantage They are sufficiently descriptive of demand processes in a large variety of settings, and at the same time, they are simple enough to be embedded into inventory decision models without making them virtually intractable. Indeed, the purpose of this section is to explain some of the complexities associated with the control of inventory for products that face the above types of demand processes, and to direct the reader to the relevant literature. 

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