Explicit solution of partitioning problems over a 1‐dimensional parameter space

We consider a class of partitioning problems where the partitioned set is a finite set of real numbers and the objective function of a partition is a function of the vector whose coordinates are the sums of the elements in each part of the given partition (the number of such parts is assumed given). We obtain an explicit solution of such partitioning problem with polynomial complexity bounds. © John Wiley & Sons, Inc. Naval Research Logistics 47: 531–540, 2000     

Effects of Nuclear Technology Export Competition on Nuclear Nonproliferation

ABSTRACT

While nuclear suppliers compete in markets, they simultaneously partner in other fields. This produces a delicate relationship between civilian nuclear programs and nuclear weapon proliferation. This study explores how export competition affects suppliers’ conditions of supply related to nuclear nonproliferation. We investigated three export cases (India, North Korea, and South Korea) and identified four effects that competition has on the conditions of supply related to nonproliferation. First, under highly competitive conditions, suppliers might hesitate to enforce the conditions of supply to avoid negotiation conflicts with recipients. Second, suppliers focus on politically and economically attractive recipients while mostly ignoring unattractive ones, perhaps allowing proliferation problems to fester out of view in marginal states. Third, suppliers can build consensus on the conditions of supply to avoid being the only party experiencing negotiation conflicts. Fourth, suppliers can constrain others from relaxing the conditions of supply to maintain economic benefits and nonproliferation norms. The first two effects accelerate proliferation while the last two promote nonproliferation. Although the extent of these effects can vary with changes in nonproliferation norms, they can contribute to our understanding of the relationship between nonproliferation and civilian nuclear programs.     

Heart analytics: Analytical modeling of cardiovascular care

Cardiovascular diseases (CVDs) are the leading cause of death and disability both in the United States and worldwide. Despite high morbidity, mortality, and cost in the United States and global healthcare systems, cardiovascular care has been understudied in the healthcare operations management literature. In this paper, we identify research opportunities for healthcare operations management scholars to aid in improving cardiovascular care. We focus on three burdensome conditions, including (1) coronary artery disease, (2) stroke, and (3) heart failure, which, collectively, lead to the vast majority of CVD‐caused mortality and disability. For each condition, we characterize a typical patient's journey in receiving cardiovascular care, elucidating key challenges in improving care and outlining research questions for healthcare operations management scholars. We close with a reference to new research opportunities that emerge as artificial intelligence is likely to transform much of cardiovascular care.     

Rare‐event component importance for the consecutive‐k system

Various indices of component importance with respect to system reliability have been proposed. The most popular one is the Birnbaum importance. In particular, a special case called uniform Birnbaum importance in which all components have the same reliability p has been widely studied for the consecutive‐k system. Since it is not easy to compare uniform Birnbaum importance, the literature has looked into the case p = ½, p → 1, or p ≥ ½. In this paper, we look into the case p → 0 to complete the spectrum of examining Birnbaum importance over the whole range of p. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 159–166, 2002; DOI 10.1002/nav.10001     

Dynamic lot‐sizing model with production time windows

We consider a dynamic lot‐sizing model with production time windows where each of n demands has earliest and latest production due dates and it must be satisfied during the given time window. For the case of nonspeculative cost structure, an O(nlogn) time procedure is developed and it is shown to run in O(n) when demands come in the order of latest production due dates. When the cost structure is somewhat general fixed plus linear that allows speculative motive, an optimal procedure with O(T⁴) is proposed where T is the length of a planning horizon. Finally, for the most general concave production cost structure, an optimal procedure with O(T⁵) is designed. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007