IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, British Columbia, Canada, 16-21 July 2006This paper investigates the effects of the mapping process employed by the GAuGE system on standard genetic operators. It is shown that the application of that mapping process transforms these operators into suitable sequencing searching tools. A practical application is analysed, and its results compared with a standard genetic algorithm, using the same operators. Results and analysis highlight the suitability of GAuGE and its operators, for this class of problems
Genetic algorithms play a significant role, as search techniques for handling complex spaces, in man...
Genetic programming (GP) can be viewed as the use of genetic algorithms (GAs) to evolve computationa...
Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined ...
IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, British Columbia, Canada, 16-21 Jul...
This thesis proposes a new representation for genetic algorithms, based on the idea of a genotype to...
Genetic Programming, 7th European Conference, EuroGP 2004, Coimbra, Portugal, 5-7 April 2004This pap...
Genetic Programming: 5th European Conference (EuroGP), Kinsale, Co. Cork, Ireland, 3-5 April 2002Thi...
Genetic and Evolutionary Computation - GECCO 2004, Genetic and Evolutionary Computation Conference, ...
The practical and theoretical success of any Evolutionary Computation (EC) application depends on th...
6th International Conference, Evolution Artificielle, EA 2003, Marseille, France, 27-30 October 2003...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
AbstractGenetic algorithms are stochastic search procedures based on randomized operators such as cr...
The 2003 Genetic and Evolutionary Computation Conference -(GECCO 2003): The 2nd Grammatical Evolutio...
Abstract—In this contribution, the use of a new genetic operator is proposed. The main advantage of ...
Genetic algorithms are stochastic search procedures based on randomized operators such as crossover ...
Genetic algorithms play a significant role, as search techniques for handling complex spaces, in man...
Genetic programming (GP) can be viewed as the use of genetic algorithms (GAs) to evolve computationa...
Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined ...
IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, British Columbia, Canada, 16-21 Jul...
This thesis proposes a new representation for genetic algorithms, based on the idea of a genotype to...
Genetic Programming, 7th European Conference, EuroGP 2004, Coimbra, Portugal, 5-7 April 2004This pap...
Genetic Programming: 5th European Conference (EuroGP), Kinsale, Co. Cork, Ireland, 3-5 April 2002Thi...
Genetic and Evolutionary Computation - GECCO 2004, Genetic and Evolutionary Computation Conference, ...
The practical and theoretical success of any Evolutionary Computation (EC) application depends on th...
6th International Conference, Evolution Artificielle, EA 2003, Marseille, France, 27-30 October 2003...
Genetic algorithm (GA) is a well known algorithm applied to a wide variety of optimization problems ...
AbstractGenetic algorithms are stochastic search procedures based on randomized operators such as cr...
The 2003 Genetic and Evolutionary Computation Conference -(GECCO 2003): The 2nd Grammatical Evolutio...
Abstract—In this contribution, the use of a new genetic operator is proposed. The main advantage of ...
Genetic algorithms are stochastic search procedures based on randomized operators such as crossover ...
Genetic algorithms play a significant role, as search techniques for handling complex spaces, in man...
Genetic programming (GP) can be viewed as the use of genetic algorithms (GAs) to evolve computationa...
Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined ...