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.