Name
Title | ||
|---|---|---|
Optimization in a distributed processing environment using genetic algorithms with multivariate crossover |
Abstract | ||
|---|---|---|
We set out to demonstrate the effectiveness of distributed genetic algorithms using multivariate crossover in optimizing a function of a sizable number of independent variables. Our results show that this algorithm has unique potential in optimizing such functions. The multivariate crossover meta-strategy, however, did not result in a singularly better performance of the algorithm than did simpler crossover strategies. |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1145/131214.131228 | ACM Conference on Computer Science |
Keywords | Field | DocType |
multivariate crossover,independent variable,genetic algorithm,unique potential,simpler crossover strategy,singularly better performance,sizable number,multivariate crossover meta-strategy,tuple space | Tuple space,Crossover,Transputer,Computer science,Multivariate statistics,Theoretical computer science,Distributed algorithm,Variables,Parallel lisp,Genetic algorithm,Distributed computing | Conference |
ISBN | Citations | PageRank |
0-89791-472-4 | 1 | 0.42 |
References | Authors | |
7 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aaron H. Konstam | 1 | 9 | 4.56 |
| Stephen J. Hartley | 2 | 36 | 9.51 |
| William L. Carr | 3 | 1 | 0.42 |