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Reproduction, Crossover, And Mutation Of Genetic Algorithm Operations

1235 words - 5 pages

Genetic Algorithm Operations
The basic GA that can produce acceptable results in many practical problems is composed of three operations:
a. Reproduction
b. Crossover
c. Mutation
The reproduction process is to allow the genetic information, stored in the good fitness for survive the next generation of the artificial strings, whereas the population's string has assigned a value and its aptitude in the object function. This value has the probability of being chosen as the parent in the reproduction process of a new generation.

The crossover is a process is divided into segments, which are exchanged with the one segments with the another string. With these process two new strings different to those that produced they are generated. It is necessary to clarify that the choice of strings crossed inside those that were chosen previously in the reproduction process is random. From the point of view of problem optimization, it is equal to the exploitation of an area of the parameters space.

The mutation is manifested with a small change in the genetic string of the individuals. In the case of artificial genetic strings, the mutation is equal to a change in the elementary portion (allele) of the individuals’ code. The mutation takes place with characteristics different to those that the individuals had at the beginning, characteristics that didn't possibly exist in the population. From the point of view of problem optimization, it is equal to a change of the search area in the parameters space.

Genetic algorithm basic parameters
The convergence of the GA to a suitable solution depends on its basic parameter like reproduction, crossover, mutation, selection and population; which to find a relationship among them to maintain search robustness has been the subject of diverse studies [4], [6] and [11]. These studies have focused on the relationship between the mutation values and convergence; to the relationship between the population's size and the crossover probability values, respectively; and to the relationship among good
Population’s size, crossover probability and selection. These studies have also focused on specific simplified problems, therefore not making it possible to use the results in practical problems. For the above-mentioned reasons it is necessary to carry out convergence tests with varying values, taking into account that the population's size, the mutation probability and the crossover probability are related for the determination of the best control parameters values. An appropriate approach [9] to begin a search is to consider population size between 30 and 50 individuals, a crossover probability of about and a smaller mutation probability of about 0.01.

1.2 The Problem Statement

Arc welding is a major bonding technique in the industries. These days, industries are using very large amount of this weld to join a part of stuffs. This is because it is difficult to estimate the welding parameters correctly. Arc welding is a very...

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