The aim of this project is to analyse and develop algorithms (for NP- hard problems) that have a high probability of success. Here, Success means solving the problem exactly or, in the case of optimization problems, to within a small margin of error. A second aim is to improve the complexity, and to extend the application, of a recently developed randomized algorithm for approximating the volume of convex bodies. Generally, graph theoretic problems, packing problems and integer programming will be studied in the context of parallel, as well as serial, algorithms. Pseudo-random inputs and randomized algorithms that use pseudo-random numbers will also be considered.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Communication Foundations (CCF)
Type
Standard Grant (Standard)
Application #
8900112
Program Officer
Dana S. Richards
Project Start
Project End
Budget Start
1989-07-01
Budget End
1991-12-31
Support Year
Fiscal Year
1989
Total Cost
$58,609
Indirect Cost
Name
Carnegie-Mellon University
Department
Type
DUNS #
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213