Abstract:
deal Coded Genetic Algorithm, RCGA, is the type of GA whichcrossover operations are defined for RCGA. One usable crossover for this kind of GA is to consider its chromosomes simply as bit strings and utilize the same operations as Binary Coded GA In this paper, we attempt to show that this kind of crossover can not hasten the convergence process unless the break points fall at the boundaries of parameters in the chromosome.
Machine summary:
One usable crossover for this kind of GA is to consider its chromosomes simply as bit strings and utilize the same operations as Binary Coded GA In this paper, we attempt to show that this kind of crossover can not hasten the convergence process unless the break points fall at the boundaries of parameters in the chromosome.
Abstract - Keywords: BCGA, Convergence Time, Crossover, Genetic Algorithm, RCGA, Real Numbers INTRODUCTON Genetic Algorithm is a search methodology invented by Holland ], which is inspired by the natural genetic theory.
In other words, breaking a real parameter from its middle not only does not improve the convergence time of the algorithm, but also can result in an algorithm slower than the simple GA without crossover.
The section, “Practical Test,” provides an empirical study where the inefficiency of the crossover operator, used with no regard to the significance of the binary digits and the border between the actual real variables, is shown via two benchmark examples.
Holland [8) represents a theory for the GA stating that the number of fitter schemas is increasing during the process of the Genetic Algorithm.
Our conjecture that crossover operations, which break down a gene in the middle, not only fail to improve the speed of the search process, but also slow it down, has been tested via two benchmark examples.
The use of crossover operator without paying any attention to the boundary between the real numbers will weaken the genetic motivation of the algorithm.