Volume 20 No 22 (2022)
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Implementation and Analysis for Efficient Selection of Fitness in Genetic Algorithm for Mobile Ad-hoc Networks
Dr N Shyam Sunder Sagar
The objective of this paper is to provide an introduction to genetic algorithm and its basic functionality. The basic operations involved in genetic algorithm are selection, crossover and mutation. It evolves around Darwin’s theory which states that “survival of the fittest”. Fitness refers not only to an organism’s strength or athletic ability, but rather the ability to survive and reproduce. Efficient methods for fitness selections while route selection process is reviewed based on the strategies for shortest path methods. Comparative analysis and the best fit implementations are suggested for Adhoc Networks which do not have any fixed architecture
Genetic algorithm, RIGA, MEGA, MRIGA, selection, crossover, mutation
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