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Study of Different Selection Strategies for Implementing Optimization Problem


Pooja , Modern Institute of Engg. & Technology, Mohri


Genetic Algorithm (GA), Fitness, Roulette Wheel Selection, Rank Selection, Tournament Selection, Elitism Selection, Hybrid selection


Genetic algorithm is a search technique used in computing to generate useful true or approximate solutions to optimization and search problems like travelling salesman problem, Dejong's Function, job scheduling problems. Selection phase play an important role in genetic algorithm to get better solutions. Selection is the phase of genetic algorithm in which we select the individual (chromosome) based upon the fitness value. The goodness of each individual depand on its fitness. Fitness can be determined by an objective function. Different selection methods are applied on these objective functions to determine the fitness of each individual. Initialization, selection, crossover and mutation are four main operation of GA. The aim of this paper is to study and compare different types of selection methods used in Genetic algorithm.

Other Details

Paper ID: IJSRDV3I2536
Published in: Volume : 3, Issue : 2
Publication Date: 01/05/2015
Page(s): 821-825

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