3165 search results - page 18 / 633 » Introduction to genetic algorithms |
GECCO
2000
Springer
15 years 1 months ago
2000
Springer
Traditional Genetic Algorithms (GA) use crossover and mutation as the main genetic operators to achieve population diversity. Previous work using a biologically inspired genetic o...
70
Voted
CEC
2008
IEEE
15 years 4 months ago
2008
IEEE
— In recent years, several approaches have been developed for genetic algorithms to enhance their performance in dynamic environments. Among these approaches, one kind of methods...
GECCO
2004
Springer
15 years 3 months ago
2004
Springer
Estimation of distribution algorithms (EDA) are similar to genetic algorithms except that they replace crossover and mutation with sampling from an estimated probability distributi...
DEXAW
2008
IEEE
15 years 4 months ago
2008
IEEE
Linear Ordering Problem (LOP) is a well know optimization problem attractive for its complexity (it is a NPhard problem), rich collection of testing data and variety of real world...
PPSN
2004
Springer
15 years 3 months ago
2004
Springer
This article describes a new model of probability density function and its use in estimation of distribution algorithms. The new model, the distribution tree, has interesting prope...