The goal of this project is to develop algorithms and prototype software for solving large-scale mixed-integer programs and to develop application routines for solving problems that arise in distribution, manufacturing, production scheduling and resource allocation. The motivation behind this research is the tremendous demand for efficient and robust mixed-integer programming algorithms in the preceding domains. A Mixed-Integer Optimizer (Minto) system was developed by these researchers in prior projects. The MINTO system allows a researcher to customize general mixed- integer optimization code through application routines and concentrate on problem specifics rather that implementation details of tools like linear programming. The project will research methods to strengthen the capabilities of MINTO. It will also research the development of the application routines for generic problems in distribution, scheduling, manufacturing and resource allocation. Real application data will be used to test the customized systems.

Agency
National Science Foundation (NSF)
Institute
Division of Civil, Mechanical, and Manufacturing Innovation (CMMI)
Application #
9115768
Program Officer
Lawrence M. Seiford
Project Start
Project End
Budget Start
1992-04-15
Budget End
1997-03-31
Support Year
Fiscal Year
1991
Total Cost
$500,000
Indirect Cost
Name
Georgia Tech Research Corporation
Department
Type
DUNS #
City
Atlanta
State
GA
Country
United States
Zip Code
30332