Client: Lockheed Martin Missiles and Fire Control
Team: Stephen Beckert, Brandon Joslin, Pierce, Meier
Faculty Advisor: Dr. Barr
Year: 2010
Documents: Final Report, Presentation
Lockheed Martin presented us with a project more exciting than we could ever imagine: aiding the research into ways to model the effects of an Electromagnetic Pulse (EMP). EMP is extremely devastating and can be caused by both natural and man-made events. EMP primarily affects electronic devices, rendering them useless or destroyed. Since the United States is heavily dependent on electronic interfaces, we are extremely vulnerable to this effect. In addition to this vulnerability to the EMP effect, the United States has a complex system of connected critical infrastructures that have not been studied as interrelated systems. This presents a major problem, how can one forecast the possible failures of such a massive complex system? Read more…
Categories: Computational probability, Dallas-Ft. Worth Area, Defense, Energy, Final report, Forecasting, Government, Integer programming, Nonlinear programming, Operations, Planning, Presentation, Reliability analysis, Scheduling, Simulation, United States, Video Tags:
Award Winner: Omega Rho National
Student Project Competition
Client: Quest Resource, Inc.
Team: John Jarvis, Claudia Johnson, Liana Vetter
Faculty advisor: Barr Year: 2004
Documents: Final report (Word), final presentation (PPT)
Currently, Quest guarantees about 85% of its gas through monthly contracts, while selling the remaining at the daily price. The amount to guarantee per sale point per month is a major decision within Quest. The motivation for Quest to optimize this process is two-fold. First, by paying close attention to past production, optimization can help assure that Quest will rarely produce under their monthly guarantee and will never incur a penalty for that underproduction. Second, through researching the historical relationship between Quest’s contract prices and the corresponding market prices for each month, Quest can better estimate the contract volume that will maximize revenue. Read more…