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TSMC
2002
93views more  TSMC 2002»
13 years 7 months ago
Statistical analysis of the main parameters involved in the design of a genetic algorithm
Abstract--Most genetic algorithm (GA) users adjust the main parameters of the design of a GA (crossover and mutation probability, population size, number of generations, crossover,...
Ignacio Rojas, Jesús González, H&eac...
GECCO
2006
Springer
135views Optimization» more  GECCO 2006»
13 years 11 months ago
A tree-based genetic algorithm for building rectilinear Steiner arborescences
A rectilinear Steiner arborescence (RSA) is a tree, whose nodes include a prescribed set of points, termed the vertices, in the first quadrant of the Cartesian plane, and whose tr...
William A. Greene
GECCO
2004
Springer
104views Optimization» more  GECCO 2004»
14 years 28 days ago
Optimization of Constructive Solid Geometry Via a Tree-Based Multi-objective Genetic Algorithm
This paper presents the multi-objective evolutionary optimization of three-dimensional geometry represented via constructive solid geometry (CSG), a binary tree of boolean operatio...
Karim Hamza, Kazuhiro Saitou
AUSAI
2007
Springer
14 years 1 months ago
The Detrimentality of Crossover
The traditional concept of a genetic algorithm (GA) is that of selection, crossover and mutation. However, a limited amount of data from the literature has suggested that the nich...
Andrew Czarn, Cara MacNish, Kaipillil Vijayan, Ber...
AIR
1998
103views more  AIR 1998»
13 years 7 months ago
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Abstract. Genetic algorithms play a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc...
Francisco Herrera, Manuel Lozano, José L. V...