Bounding separable recourse functions with limited distribution information

The recourse function in a stochastic program with recourse can be approximated by separable functions of the original random variables or linear transformations of them. The resulting bound then involves summing simple integrals. These integrals may themselves be difficult to compute or may require more information about the random variables than is available. In this paper, we show that a special class of functions has an easily computable bound that achieves the best upper bound when only first and second moment constraints are available.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44185/1/10479_2005_Article_BF02204821.pd

Identifying hospital antimicrobial resistance targets via robust ranking

<p>We develop a robust ranking procedure to uncover trends in variation in antibiotic resistance (AR) rates across hospitals for some antibiotic-bacterium pairs over several years. We illustrate how the method can be used to detect potentially dangerous trends and to direct attention to hospitals’ management practices. A robust method is indicated because some unusual reported resistance rates may be due to measurement protocol differences and not any real difference in AR rates. Our proposed method is less sensitive to outlier observations than other robust methods. The application on real AR data shows how a dangerous trend in a particular AR rate would be detected. Our results indicate the potential benefits of systematic AR rate collection and AR reporting systems across hospitals.</p

\u3ci\u3eComputer Science and Operations Research: New Developments in Their Interfaces\u3c/i\u3e

Editors: Osman Balci, Ramesh Sharda, and Stavros A. Zenios Chapter, Preprocessing Schemes and a Solution Method for the Convex Hull Problem in a Multidimensional Space, co-authored by Betty Love, UNO faculty member. Chapter, On Reporting the Speedup of Parallel Algorithms: A Survey of Issues and Experts, co-authored by Betty Love, UNO faculty member. The interface of Operation Research and Computer Science - although elusive to a precise definition - has been a fertile area of both methodological and applied research. The papers in this book, written by experts in their respective fields, convey the current state-of-the-art in this interface across a broad spectrum of research domains which include optimization techniques, linear programming, interior point algorithms, networks, computer graphics in operations research, parallel algorithms and implementations, planning and scheduling, genetic algorithms, heuristic search techniques and data retrieval.https://digitalcommons.unomaha.edu/facultybooks/1289/thumbnail.jp