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AbstractThis paper shows that one of the fundamental results of inventory theory is valid under conditions much broader than those treated previously. The result characterizes the distributions of inventory level and inventory position in the standard, continuous‐time model with backorders, and leads to the relatively easy calculation of key performance measures. We treat both fixed and random leadtimes, and we examine both stationary and limiting distributions under different assumptions. We consider demand processes described by several general classes of compound‐counting processes and a variety of order policies. For the stochastic‐leadtime case we provide the first explicit proof of the result, assuming the leadtimes are generated according to a specific, but plausible, scenario.

AbstractTransportation problems with uncertain demands are useful applied models themselves, and also they represent in a formal way the problem of estimating demands for use in deterministic models. We consider the effects of using a small, aggregate model of this type in place of a larger, more detailed one. Formulation of the aggregate objective function turns out to depend on how one chooses to use (disaggregate) the solution; several alternative methods are examined. Bounds are derived on the error induced by the approximation, thus facilitating comparison of alternative aggregations. We also consider the problem of estimating demands for an aggregate‐level deterministic problem. In a specific sense, it is often not the case (as one might expect) that such aggregate demands are easier to estimate than the detailed demands. This is because aggregation and centralization are not the same thing.

AbstractThis article generalizes the models in Guo and Zipkin, who focus on exponential service times, to systems with phase‐type service times. Each arriving customer decides whether to stay or balk based on his expected waiting cost, conditional on the information provided. We show how to compute the throughput and customers' average utility in each case. We then obtain some analytical and numerical results to assess the effect of more or less information. We also show that service‐time variability degrades the system's performance. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

AbstractConsider a central depot that supplies several locations experiencing random demands. Periodically, the depot may place an order for exogenous supply. Orders arrive after a fixed leadtime, and are then allocated among the several locations. Each allocation reaches its destination after a further delay. We consider the special case where the penalty‐cost/holding‐cost ratio is constant over the locations. Several approaches are given to approximate the dynamic program describing the problem. Each approach provides both a near‐optimal order policy and an approximation of the optimal cost of the original problem. In addition, simple but effective allocation policies are discussed.

AbstractThis article analyzes a capacity/inventory planning problem with a one‐time uncertain demand. There is a long procurement leadtime, but as some partial demand information is revealed, the firm is allowed to cancel some of the original capacity reservation at a certain fee or sell off some inventory at a lower price. The problem can be viewed as a generalization of the classic newsvendor problem and can be found in many applications. One key observation of the analysis is that the dynamic programming formulation of the problem is closely related to a recursion that arises in the study of a far more complex system, a series inventory system with stochastic demand over an infinite horizon. Using this equivalence, we characterize the optimal policy and assess the value of the additional demand information. We also extend the analysis to a richer model of information. Here, demand is driven by an underlying Markov process, representing economic conditions, weather, market competition, and other environmental factors. Interestingly, under this more general model, the connection to the series inventory system is different. © 2012 Wiley Periodicals, Inc. Naval Research Logistics 2012

AbstractIn this paper, we extend the results of Ferguson M. Naval Research Logistics 50, 2003, 917–936. on an end‐product manufacturer's choice of when to commit to an order quantity from its parts supplier. During the supplier's lead‐time, information arrives about end‐product demand. This information reduces some of the forecast uncertainty. While the supplier must choose its production quantity of parts based on the original forecast, the manufacturer can wait to place its order from the supplier after observing the information update. We find that a manufacturer is sometimes better off with a contract requiring an early commitment to its order quantity, before the supplier commits resources. On the other hand, the supplier sometimes prefers a delayed commitment. The preferences depend upon the amount of demand uncertainty resolved by the information as well as which member of the supply chain sets the exchange price. We also show conditions where demand information updating is detrimental to both the manufacturer and the supplier. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005