Genetic Algorithm Research Paper
Genetic Algorithms(GAs)
The theory of Genetic Algorithms first was envisaged by Professor John Holland of the University of Michigan in the early 1970s in one of its seminal work. Two main goals of that work were (1) explaining the adaptive processes of the natural system and (2) designing software that maintains the idea of natural systems [5]. The main concept of Genetic Algorithms is the power of evolution using to solve search and optimization problems. Genetic Algorithms are adaptive heuristic search and optimization methods which mimic the evolutionary ideas of natural selection and natural genetics. Moreover, they are part of Evolutionary Algorithms. Consequently, they represent an intelligent use of a random search used to solve different optimization
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In GAs, Selection is the action of choosing among a range of things the best or most suitable one to fulfill our aims. Also in this field, the meaning of selection is to choose the appropriate parent, gene, chromosomes of the problem.
Let’s consider that one solution is an individual in the population. Consequently, the population is created from a large number of solutions. Some of them may be good ones, some others may be better but there can be also bad results. Under such condition, some individuals (chromosomes) can be taken with traits that fit the needs and those individuals will become parents. New parents will help us to create new individuals for the next population. Successors will be superior to their parents, with the solution to the problem with wanted treats. This is the selection that is made to obtain better results and as a result of selection occurs evolution. An important fact to be mentioned is that is not a certainty that the genetic algorithm will return the best solution, it is true that this algorithm will return to the user the best solution obtained until the program has
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