A model for use in the rationing of inventory during lead time

While the traditional solution to the problem of meeting stochastically variable demands for inventory during procurement lead time is through the use of some level of safety stock, several authors have suggested that a decision be made to employ some form of rationing so as to protect certain classes of demands against stockout by restricting issues to other classes. Nahmias and Demmy [10] derived an approximate continuous review model of systems with two demand classes which would permit an inventory manager to calculate the expected fill rates per order cycle for high-priority, low-priority, and total system demands for a variety of parameters. The manager would then choose the rationing policy that most closely approximated his fill-rate objectives. This article describes a periodic review model that permits the manager to establish a discrete time rationing policy during lead time by prescribing a desired service level for high-priority demands. The reserve levels necessary to meet this level of service can then be calculated based upon the assumed probability distributions of high- and low-priority demands over lead time. The derived reserve levels vary with the amount of lead time remaining. Simulation tests of the model indicate they are more effective than the single reserve level policy studied by Nahmias and Demmy.     

Discount pricing policies for inventories subject to declining demand

Until only recently, the mechanism behind determining item price has been ignored and the discount price taken as a given in quantity-discount inventory decision problems. Inventory subject to declining demand further complicates both pricing and replenishment decisions. This article provides the vendor with the means for optimally determining both the discount price and replenishment order frequency for all buyers in the system in an environment of declining demand. In the multiple-buyer case, we provide an efficient algorithm for classifying buyers into homogeneous subgroups to further enhance joint cost savings among all system participants.     

Multiechelon inventory systems with lateral supply

We develop approximations to estimate the expected backorders in a multiechelon system in which lateral supply actions between bases are allowed when a backorder occurs. These approximations are easy to compute, and the average absolute error over a wide range of parameter values is less than 4% when items are depot repairable, even when bases are dissimilar. With lateral supply, backorder reductions of 30-50% are not uncommon, and a 72% reduction was observed in two cases. Lateral supply becomes more important with low demand rates. A similar approach was unsuccessful for base-repairable items. However, lateral supply has a beneficial effect only when the lateral supply time is very short, 1/4 or less of the average base repair time. Even in such cases lateral supply is unlikely to be important in an actual application, because base management can expedite repair of critical items.     

Scheduling with earliness and tardiness penalties

We show that the deterministic nonpreemptive scheduling problem with earliness and tardiness penalties can be solved in polynomial time for certain forms of an objective function provided that a certain optimization problem can be solved. We give instances where this problem has a solution and show that this generalizes several results from the literature. These results do not require symmetric penalization and the penalty functions need only be lower semicontinuous.     

Optimality of control limit policies in replacement models

We study a class of replacement models for systems subject to deterioration. The objective is to determine an optimal replacement policy that minimizes the average operating costs of the system. We use a parametric analysis to establish sufficient conditions for the optimality of control limit policies. This work generalizes several existing results for optimal replacement models in the literature. © 1992 John Wiley & Sons, Inc.     

Single‐machine scheduling with deadlines to minimize the total weighted late work

We consider scheduling a set of jobs with deadlines to minimize the total weighted late work on a single machine, where the late work of a job is the amount of processing of the job that is scheduled after its due date and before its deadline. This is the first study on scheduling with the late work criterion under the deadline restriction. In this paper, we show that (i) the problem is unary NP‐hard even if all the jobs have a unit weight, (ii) the problem is binary NP‐hard and admits a pseudo‐polynomial‐time algorithm and a fully polynomial‐time approximation scheme if all the jobs have a common due date, and (iii) some special cases of the problem are polynomially solvable.     

Designing and pricing menus of extended warranty contracts

Extended warranties provide “piece of mind” to a consumer in that product failures which occur after the base warranty expires are rectified at little or no cost. They also provide an additional source of revenue for manufacturers or third‐party providers, such as retailers or insurance providers, and help cultivate consumer loyalty. In this article, we analyze a number of extended warranty contracts which differ in design, including restrictions on deferrals and renewals. With the use of dynamic programming, we compute the optimal strategy for a consumer with perfect information and determine the optimal pricing policy for the provider given the consumer's risk characterization. We also provide insight into when different contracts should be issued. Finally, we illustrate how profits can be dramatically increased by offering menus of warranty contracts, as opposed to stand alone contracts, with the use of integer programming. Surprisingly, risk‐taking consumers provide the greatest benefit to offering menus. These insights can help a company develop a comprehensive warranty planning strategy for given products or product lines. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009