Robert R. Meyer
Professor of Computer Sciences and member of the Center for the
Ph.D., University of Wisconsin, 1968
Computer Sciences Department
University of Wisconsin
1210 W. Dayton St.
Madison, WI 53706-1685
Telephone: (608) 262-1204
Fax: (608) 262-9777
Linear and nonlinear network optimization, parallel algorithms
for large-scale optimization
Most large-scale optimization problems exhibit substructures that
make possible solutions via algorithms with a high degree of parallelism.
Such substructures include quasi-independent blocks of constraints
for different commodities or time periods or scenarios, and geographically-disjoint
components in approximating solutions. In the case of network
optimization, decomposition into approximating linear network
subproblems is particularly attractive because of the corresponding
very fast solution techniques. The emphases of my research have
been the development of new parallel optimization algorithms that
utilize these features and techniques such as genetic algorithms
to take advantage of distributed computing environments in order
to efficiently solve linear and nonlinear network optimization
problems containing millions of variables.
Sample Recent Publications
Minimizing perimeter for domain decomposition
Brachytherapy optimization for prostate cancer treatment
demand: optimal caching
Recent papers of
UW mathematical programming group
firstname.lastname@example.org to report errors.