Name
Abstract | ||
|---|---|---|
Abstract This paper is concerned with the application of gen etic algorithms to optimization problems over several real parameters. It is shown that k-point crossover (for k small relative to the number,of parameters) can be viewed as a crossover operation on the vector of parameters plus perturbations of some,of the parameters. Mutation can also be co nsidered as a perturbation of some,of the parameters. This suggests a genetic algorithm that uses real parameter vectors as chromosomes, real parameters as genes, and real numbers as allel es. Such an algorithm is proposed with two possible crossover methods. Schemata are defined f or this algorithm, and it is shown that Holland’s Schema theorem holds for one of these cro ssover methods. Experimental results are given that indicate that this algorithm with a mixt ure of the two crossover methods,outperformed the binary-coded genetic algorithm on 7 of 9 test p roblems. Keywords: optimization, genetic algorithm, evolution |
Year | Venue | DocType |
|---|---|---|
1990 | FOGA | Conference |
Citations | PageRank | References |
2 | 0.66 | 5 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alden H. Wright | 1 | 330 | 45.58 |