DocumentCode
342882
Title
Crossover operators that improve offspring fitness
Author
Mohan, Chilukuri K.
Author_Institution
Centre for Sci. & Technol., Syracuse Univ., NY, USA
Volume
2
fYear
1999
fDate
1999
Abstract
Fine-honing the crossover operator to produce higher fitness children is shown to result in improved genetic search. To illustrate this, two new general-purpose crossover operators are described. These operators require more computation time than traditional crossover operators, but the number of fitness evaluations and the overall amount of time spent by the genetic algorithm (to obtain solutions of desired near-optimal quality) is reduced significantly
Keywords
genetic algorithms; search problems; computation time; fitness evaluations; general-purpose crossover operators; genetic algorithm; genetic search; higher fitness children; offspring fitness improvement; Algorithm design and analysis; Approximation methods; Computer science; Evolutionary computation; Genetics; Optimization methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location
Washington, DC
Print_ISBN
0-7803-5536-9
Type
conf
DOI
10.1109/CEC.1999.782667
Filename
782667
Link To Document