In this paper, we deal with promising crossover operators developed in the genetic algorithm (GA) and analyze the performance of these crossovers on the traveling salesman problem (TSP) which is one of the most popular NP-hard problems. Many crossovers that efficiently generate good solutions have b
β¦ LIBER β¦
Genetic algorithm crossover operators for ordering applications
β Scribed by P.W. Poon; J.N. Carter
- Publisher
- Elsevier Science
- Year
- 1995
- Tongue
- English
- Weight
- 794 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0305-0548
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Performance analysis for crossover opera
β
Kengo Katayama; Hisayuki Hirabayashi; Hiroyuki Narihisa
π
Article
π
1999
π
John Wiley and Sons
π
English
β 717 KB
Hybrid crossover operators with multiple
β
Ana M. SΓ‘nchez; Manuel Lozano; Pedro Villar; Francisco Herrera
π
Article
π
2009
π
John Wiley and Sons
π
English
β 246 KB
Most real-coded genetic algorithm research has focused on developing effective crossover operators, and as a result, many different types of crossover operators have been proposed. Some forms of crossover operators are more suitable to tackle certain problems than others, even at the different stage
Hybrid crossover operators for real-code
β
F. Herrera; M. Lozano; A.M. SΓ‘nchez
π
Article
π
2004
π
Springer
π
English
β 404 KB
The effects of two new crossover operato
β
Mustafa Kaya
π
Article
π
2011
π
Elsevier Science
π
English
β 698 KB
Robust confidence intervals applied to c
β
Domingo Ortiz-Boyer; CΓ©sar HervΓ‘s-MartΓnez; NicolΓ‘s GarcΓa-Pedrajas
π
Article
π
2007
π
Springer
π
English
β 685 KB
Improved genetic operator for genetic al
β
Lin Feng; Yang Qi-wen
π
Article
π
2002
π
SP Zhejiang University Press
π
English
β 459 KB