A Comparative Analysis of Selection Scheme
Sonali Gandhi1, Deeba Khan2, Vikram Singh Solanki3
1Sonali Gandhi, Computer Science Engineering, Indore Institute of Science and technology, Indore, India.
2Deeba Khan, Computer Science Engineering, Indore Institute of Science and Technology ,Indore, India.
3Vikram Singh Solanki, Computer Science Engineering, Indore Institute of Science and Technology, Indore, India
Manuscript received on September 01, 2012. | Revised Manuscript received on September 02, 2012. | Manuscript published on September 05, 2012. | PP: 131-134 | Volume-2 Issue-4, September 2012. | Retrieval Number: D0915072412/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Selection scheme is an important part of genetic algorithms, which chooses a chromosome from the current generation’s population for inclusion in the next generation’s population, is the main subject of this paper. A selection operator selects the best chromosome using fitness function. Selection scheme is used to improve chances of the survivals of the fittest individuals. This paper recommends a number of selection (reproduction) methods most commonly used in genetic algorithms and analyzes them. These methods are: roulette wheel, rank selection, Boltzmann selection, tournament selection, steady state selection and elitism are compared on the basis of performance and takeover time computations .the analysis provides approximate or exact solutions. The paper recommends practical application and analyses a number of ways for more detailed analytical investigation of selection schemes.
Keywords: Roulette Wheel, Rank selection, Boltzmann Selection, Tournament selection, Steady State Selection, Elitism.