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GECCO
2004
Springer
126views Optimization» more  GECCO 2004»
13 years 10 months ago
A Gene Based Adaptive Mutation Strategy for Genetic Algorithms
In this study, a new mechanism that adapts the mutation rate for each locus on the chromosomes, based on feedback obtained from the current population is proposed. Through tests us...
Sima Uyar, Sanem Sariel, Gülsen Eryigit
SAC
2006
ACM
13 years 10 months ago
Adaptive mutation with fitness and allele distribution correlation for genetic algorithms
In this paper, a new gene based adaptive mutation scheme is proposed for genetic algorithms (GAs), where the information on gene based fitness statistics and on gene based allele...
Shengxiang Yang, Sima Uyar
BMEI
2008
IEEE
13 years 11 months ago
Adaptive Gene Expression Programming Algorithm Based on Cloud Model
Standard Gene Expression Programming(GEP) works with fixed rate of mutation and crossover, ignoring the variation of the individual fitness, hence it works in the local optimum st...
Yue Jiang, Chang-jie Tang, Haichun Zheng, Chuan Li...
APIN
2000
120views more  APIN 2000»
13 years 4 months ago
Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Francisco Herrera, Manuel Lozano
EPS
1997
Springer
13 years 9 months ago
An Individually Variable Mutation-Rate Strategy for Genetic Algorithms
Abstract. In Neo-Darwinism, mutation can be considered to be unaffected by selection pressure. This is the metaphor generally used by the genetic algorithm for its treatment of the...
Stephen A. Stanhope, Jason M. Daida