On the (S − 1, S) lost sales inventory model with priority demand classes

In this paper an inventory model with several demand classes, prioritised according to importance, is analysed. We consider a lot‐for‐lot or (S ? 1, S) inventory model with lost sales. For each demand class there is a critical stock level at and below which demand from that class is not satisfied from stock on hand. In this way stock is retained to meet demand from higher priority demand classes. A set of such critical levels determines the stocking policy. For Poisson demand and a generally distributed lead time, we derive expressions for the service levels for each demand class and the average total cost per unit time. Efficient solution methods for obtaining optimal policies, with and without service level constraints, are presented. Numerical experiments in which the solution methods are tested demonstrate that significant cost reductions can be achieved by distinguishing between demand classes. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 593–610, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10032     

Sensitivity curves for effective project management

A key problem in project management is to decide which activities are the most important to manage and how best to manage them. A considerable amount of literature has been devoted to assigning “importance” measures to activities to help with this important task. When activity times are modeled as random variables, these activity importance measures are more complex and difficult to use. A key problem with all existing measures is that they summarize the importance in a single number. The result is that it is difficult for managers to determine a range of times for an activity that might be acceptable or unacceptable. In this paper, we develop sensitivity curves that display the most useful measures of project performance (in terms of schedule) as a function of an activity's time. The structure of the networks allows us to efficiently estimate these curves for all desired activities, all desired time ranges, and all desired measures in a single set of simulation runs. The resulting curves provide insights that are not available when considering summarized measures alone. Chief among these insights is the ability to identify an acceptable range of times for an activity that will not lead to negative scheduling consequences. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 481–497, 2003     

Age replacement policies in two time scales

We develop and estimate optimal age replacement policies for devices whose age is measured in two time scales. For example, the age of a jet engine can be measured in the number of flight hours and the number of landings. Under a single‐scale age replacement policy, a device is replaced at age τ or upon failure, whichever occurs first. We show that a natural generalization to two scales is to replace nonfailed devices when their usage path crosses the boundary of a two‐dimensional region M, where M is a lower set with respect to the matrix partial order. For lifetimes measured in two scales, we consider devices that age along linear usage paths. We generalize the single‐scale long‐run average cost, estimate optimal two‐scale policies, and give an example. We note that these policies are strongly consistent estimators of the true optimal policies under mild conditions, and study small‐sample behavior using simulation. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 592–613, 2003.     

Deviant globalization: the application of strategic landpower*

In both Afghanistan and Iraq, US landpower was able to gain control rapidly over terrain. However, that control ebbed as US presence weakened. Non-state actors, such as the Taliban, the Haqqani network, the Islamic State, and Al Qaeda, gained control of segments of the population. Transnational Criminal Organizations capitalized on this permissive environment to strengthen their networks, often eroding the legitimacy of the host nation government, fueling regional instability, and, ultimately, undermining US policy objectives. The proliferation of deviant globalization, or the connectedness of subversive elements, is a key indicator of future conflict. Strategic landpower is uniquely positioned to influence the physical, psychological, economic, and social interactions of various non-state actors and their association with deviant globalization. It is no longer enough to seize and hold terrain. Landpower must also have the capability to influence the actions and attitudes of populations on that terrain wherever and whenever these interactions occur.     

Auctions in the post‐change‐order period

A change order is frequently initiated by either the supplier or the buyer, especially when the contract is long‐term or when the contractual design is complex. In response to a change order, the buyer can enter a bargaining process to negotiate a new price. If the bargaining fails, she pays a cancellation fee (or penalty) and opens an auction. We call this process the sequential bargaining‐auction (BA). At the time of bargaining, the buyer is uncertain as to whether the bargained price is set to her advantage; indeed, she might, or might not, obtain a better price in the new auction. To overcome these difficulties, we propose a new change‐order‐handling mechanism by which the buyer has an option to change the contractual supplier after bargaining ends with a bargained price. We call this the option mechanism. By this mechanism, the privilege of selling products or services is transferred to a new supplier if the buyer exercises the option. To exercise the option, the buyer pays a prespecified cash payment, which we call the switch price, to the original supplier. If the option is not exercised, the bargained price remains in effect. When a switch price is proposed by the buyer, the supplier decides whether or not to accept it. If the supplier accepts it, the buyer opens an auction. The option is exercised when there is a winner in the auction. This article shows how, under the option mechanism, the optimal switch price and the optimal reserve price are determined. Compared to the sequential BA, both the buyer and the supplier benefit. Additionally, the option mechanism coordinates the supply chain consisting of the two parties. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 248–265, 2015     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.