2009 Student Poster Presentations

Stochastic Programming Models for Wildfire Initial Response Planning

Julian A. Gallego

Industrial and Systems Engineering

Texas A&M University

We present two stochastic programming models for initial attack: standard response model (SRM) and explicit fire growth response model (ERM). The SRM assumes a known standard response needed to contain a fire of given size, while the EFGRM considers fire behavior characterized as fire perimeter and burned area at discrete time intervals over the initial response period. We discuss solution methods for the models and report on a computational study using instances based on actual data for one of the Texas Forest Service fire planning unit in East Texas.

Computationally Tractable Stochastic Integer Programming Models for Air Traffic Flow Management

Charles N. Glover

Applied Mathematics and Scientific Computation Program

Institute of Systems Research

University of Maryland

A primary objective of Air Traffic Flow Management (ATFM) is to ensure the overall flow of aircraft through airspace, while minimizing the impact of delays and congestion on airspace users. Much of this delay and congestion is caused by the vulnerability fo the airspace to changes in the weather, which can lower the capacities of different regions of airspace. Combine this uncertainty with the size of the airspace system and we arrive at a very complex system. This makes the development of efficient algorithms to solve ATFM problems an important and active area of research. In this prospectus, I will introduce some techniques of mathematical programming that can be used to solve ATFM problems and discuss some algorithms and mathematical models along with the research they inspire in this area.

Current Success Factors for Sustaining Kaizen Event Outcomes

Wiljeana J. Glover

Industrial and Systems Engineering Department

Virginia Polytechnic Institute and State University

A Kaizen event is a focused and structured improvement project, using a dedicated cross-functional team to improve a targeted work area, with specific goals, in an accelerated timeframe. Kaizen events have been widely reported to achieve successful results upon the conclusion of the event, however, a major obstacle for many organizations is the to sustain or improve upon the initial Kaizen event results. This research surveys the Kaizen event, work area, and post-event factors of approximately 65 Kaizen event teams across eight organizations. Multivariate data analysis methods are used to identify the factors that may influence the sustainability of Kaizen event outcomes.

Reliability Modeling and Technology Assessment for Capital Equipment Acquisition Decisions

Samuel Merriweather

Industrial and Systems Engineering

Texas A&M University

We will discuss a risk-based approach to capital equipment budgeting and acquisition supported by reliability/availability life cycle models. We are particularly concerned with technology assessment decisions where capital equipment budgets carry profound financial risk (e.g., small health care facilities) and candidate acquisitions are new technologies having little operational history.

Assortment Selection in Dual Sales Channels

Betzabe Rodriquez

Industrial and Operations Engineering

University of Michigan

We consider a build-to-order manufacturer who sells an assortment of products through both a direct channel and an independent retailer (e.g. Dell selling through BestBuy). We study the tension between the retailer's and the manufacturer's preferences regarding the retailer's assortment. We find that the retailer may wish to carry a smaller assortment in an effort to curb the manufacturer's wholesale price.

Iterative Methods for Computational Models of Acoustic Scattering

Josef Sifuentes

Computational and Applied Mathematics

Rice University

Models of acoustic scattering through inhomogeneous material is a vital component to many industrial applications, including seismic imaging in the petroleum industry, sonar and radar research in the defense industry, medical imaging and shape optimization of acoustic materials. One method of creating such models require computational techniques for computing high order approximations to Lippmann-Schwinger integral equations. Discretizations of the Lippmann-Schwinger integral equation result in large, dense, non-Hermitian matrix equations. We develop efficient, Krylov-based iterative methods for solving these equations based on analysis of the underlying integral operator and its spectrum.