This Faculty Early Career Development (CAREER) award provides funds for research and education activities to advance the theory, computations and applications of stochastic and robust integer programming. Integer decision variables are commonly used in models for decision making problems. Moreover, in real-time decision making problems, instance parameters are usually uncertain. This work will study stochastic and robust integer programming approaches to formulate and solve decision making problems with integer decision variables and uncertain parameters. The research activities include 1) studying polyhedral structures and polynomial time algorithms for fundamental problem formulations, 2) discovering new methods to integrate cutting planes with decomposition algorithms, 3) exploring cyberinfrastructure to implement the algorithms efficiently in high performance computing facilities, and 4) integrating theoretical analysis with application problems in power asset optimization, joint pricing and inventory planning, and weather forecasting and evacuation plans. The education activities include 1) promoting the practice of stochastic and robust integer programming as an efficient approach to solve decision making under uncertainty problems and 2) stimulating student interest in research in science and technology, especially in operations research.

The research and education tasks are integrated in a way that both benefit from each other. If successful, the results of the research activities will lead to methodology innovations for solving large-scale decision making under uncertainty problems and advance the utilization of cyberinfrastructure in optimization. These research outcomes will provide new methodologies that can be used to instruct the next generation of engineers on efficient optimization methods. In addition, the activities will have big impact on industry and society by disseminating advanced methodologies to practitioners and providing outreach to underrepresented minority students, through collaborations with local industry and research centers such as Center for Engineering Logistics and Distribution, Center for Analysis and Prediction of Storms, and the K20 Center.

Project Start
Project End
Budget Start
2008-08-15
Budget End
2009-07-31
Support Year
Fiscal Year
2007
Total Cost
$400,000
Indirect Cost
Name
University of Oklahoma
Department
Type
DUNS #
City
Norman
State
OK
Country
United States
Zip Code
73019