The premature convergence is the essential problem in genetic algorithms and it is strongly related to the loss of genetic diversity of the population. In this study, a new sexual selection mechanism which utilizing mate chromosome during selection proposed and then technique focuses on selecting and controlling the genetic operators by applying the fuzzy logic controller. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving benchmark problems published in the literature
Evolutionary algorithms, and genetic algorithms in particular, are generally time consuming when loo...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
In this project, I investigated whether the inclusion of frequency dependent selection in genetic al...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
The Genetic Algorithms (GAs) have been very successful in handling optimization problems which are d...
Premature convergence is a classical problem in finding optimal solution in Genetic Algorithms (GAs)...
Diversity of the population in a genetic algorithm plays an important role in impeding premature con...
Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logi...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the...
Combining numerous appropriate experts can improve the generalization performance of the group when ...
International audienceThis paper proposes a new method to design a fuzzy logic controller by genetic...
International audienceThis paper proposes a new method to design a fuzzy logic controller by genetic...
Selection for reproduction in the context of Genetic Algorithms uses only one selection scheme to se...
Evolutionary algorithms, and genetic algorithms in particular, are generally time consuming when loo...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
In this project, I investigated whether the inclusion of frequency dependent selection in genetic al...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
The fundamental problem in genetic algorithms is premature convergence, and it is strongly related t...
The Genetic Algorithms (GAs) have been very successful in handling optimization problems which are d...
Premature convergence is a classical problem in finding optimal solution in Genetic Algorithms (GAs)...
Diversity of the population in a genetic algorithm plays an important role in impeding premature con...
Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logi...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
The performance of a genetic algorithm is dependent on the genetic operators, in general, and on the...
Combining numerous appropriate experts can improve the generalization performance of the group when ...
International audienceThis paper proposes a new method to design a fuzzy logic controller by genetic...
International audienceThis paper proposes a new method to design a fuzzy logic controller by genetic...
Selection for reproduction in the context of Genetic Algorithms uses only one selection scheme to se...
Evolutionary algorithms, and genetic algorithms in particular, are generally time consuming when loo...
Genetic algorithms are adaptive methods that use principles inspired by natural population genetics ...
In this project, I investigated whether the inclusion of frequency dependent selection in genetic al...