Name
Abstract | ||
|---|---|---|
Recently, the methodologies of multi-parent crossover have been developed by performing the crossover operation with multi-parent. Some studies have indicated the high performance of multi-parent crossover on some numerical optimization problems. Here a new crossover operator has been proposed by integrating multi-parent crossover with the approach of experimental design. It is based on experimental design method in exploring the solution space that compensates the random search as in traditional genetic algorithm. By replacing the inbuilt randomness of crossover operator with a more systematical method, the proposed method outperforms the classical GA strategy on several GA benchmark problems. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-36599-0_27 | EuroGP |
Keywords | Field | DocType |
classical ga strategy,experimental design,ga benchmark problem,crossover operator,systematical method,new crossover operator,multi-parent crossover,multi-parent crossover operator,experimental design method,crossover operation,genetic algorithm,random search | Random search,Crossover,Search algorithm,Computer science,Algorithm,Operator (computer programming),Optimization problem,Genetic algorithm,Randomness | Conference |
Volume | ISSN | ISBN |
2610 | 0302-9743 | 3-540-00971-X |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kit Yan Chan | 1 | 470 | 45.36 |
| T C Fogarty | 2 | 1147 | 152.53 |