pages 1218-1223International audienceThis paper deals with the way dual genetic algorithms (dga), an extension of the standard ones, explore the search space. After a brief introduction presenting genetic algorithms and dualism, the fitness distance correlation is discussed in the context of dualism. From this discussion, a conjecture is made about the genetic heuristic used by dual genetic algorithms to explore the search space. This conjecture is reinforced by the visualization of the population centroid trajectories in the plane fitness distance. These trajectories help to point out "leg-up" behaviors, which allow the dual genetic algorithm to reach the global optimum from walks on deceptive paths
The Genetic Algorithm (GA) is a popular approach to search and optimization that has been applied to...
Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of ...
Genetic algorithms provide an alternative to traditional optimization techniques by using directed r...
Genetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. ...
Copyright @ 2003 IOS PressGenetic algorithms (GAs) are a class of search algorithms based on princip...
The development and optimisation of programs through search is a growing application area for comput...
Evolutionary algorithms are powerful techniques for optimisation whose operation principles are insp...
The ideal of designing a robust and efficient Genetic Algorithms (GAs), easy to use and applicable t...
The parallel genetic algorithm (PGA) uses two major modifications compared to the genetic algorithm....
Fitness distance correlation (FDC) has been offered as a summary statistic with apparent success in ...
In this paper, the mathematical interpretation of correlation coefficient is reviewed to explain the...
Genetic algorithms apply the biological principles of selection, mutation, and crossover to a popula...
Basic principles of evolutionary algorithms and genetic search of parameter spaces are described in ...
Data mining is the process of discovering interesting knowledge, such as patterns, associations, cha...
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solv...
The Genetic Algorithm (GA) is a popular approach to search and optimization that has been applied to...
Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of ...
Genetic algorithms provide an alternative to traditional optimization techniques by using directed r...
Genetic algorithms (GAs) are a class of search algorithms based on principles of natural evolution. ...
Copyright @ 2003 IOS PressGenetic algorithms (GAs) are a class of search algorithms based on princip...
The development and optimisation of programs through search is a growing application area for comput...
Evolutionary algorithms are powerful techniques for optimisation whose operation principles are insp...
The ideal of designing a robust and efficient Genetic Algorithms (GAs), easy to use and applicable t...
The parallel genetic algorithm (PGA) uses two major modifications compared to the genetic algorithm....
Fitness distance correlation (FDC) has been offered as a summary statistic with apparent success in ...
In this paper, the mathematical interpretation of correlation coefficient is reviewed to explain the...
Genetic algorithms apply the biological principles of selection, mutation, and crossover to a popula...
Basic principles of evolutionary algorithms and genetic search of parameter spaces are described in ...
Data mining is the process of discovering interesting knowledge, such as patterns, associations, cha...
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solv...
The Genetic Algorithm (GA) is a popular approach to search and optimization that has been applied to...
Genetic Algorithms are efficient and robust search methods that are being employed in a plethora of ...
Genetic algorithms provide an alternative to traditional optimization techniques by using directed r...