Workshop on Genetic Algorithms
G. Anderson, Ph. D.
Genetic algorithms (GAs) solve problems in a means inspired by "selective
breeding." GAs start with a random population of problem solutions;
iteratively, better solutions are selected and allowed to breed (parts
from two or more good solutions are composed to form children solutions);
inferior solutions are selected to leave the population; and the overall
fitnesses of the population members gradually increases until a suitable
solution is discovered.
The Workshop will comprise an introduction to techniques of genetic
algorithms and the types of problem solving GAs are applicable for.
Special emphasis will be placed on problems such as scheduling.
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- Peter G. Anderson, Ph. D.
- Professor, Computer Science Department
- Chief Scientist, Laboratory for Applied Computing
- Room 74-1071
- Rochester Institute of Technology
- Rochester, New York - 14623-5608
- Phone: 585-475-2979 - FAX: 585-475-5669