Comparative Analysis of Genetic Crossover Operators in Knapsack Problem

The Genetic Algorithm (GA) is an evolutionary algorithms and technique based on natural selections of individuals called chromosomes. In this paper, a method for solving Knapsack problem via GA (Genetic Algorithm) is presented. We compared six different crossovers: Crossover single point, Crossover...

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Bibliographic Details
Published in:Journal of applied science & environmental management 2017-01, Vol.20 (3)
Main Authors: HAKIMI, D, OYEWOLA, D.O, YAHAYA, Y, BOLARIN, G
Format: Article
Language:English
Subjects:
Arithmetic
Crossover
Evolutionary Algorithm
Genetic Algorithm
Heuristic
Intermediate
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Summary:The Genetic Algorithm (GA) is an evolutionary algorithms and technique based on natural selections of individuals called chromosomes. In this paper, a method for solving Knapsack problem via GA (Genetic Algorithm) is presented. We compared six different crossovers: Crossover single point, Crossover Two point, Crossover Scattered, Crossover Heuristic, Crossover Arithmetic and Crossover Intermediate. Three different dimensions of knapsack problems are used to test the convergence of knapsack problem. Based on our experimental results, two point crossovers (TP) emerged the best result to solve knapsack problem. © JASEM
ISSN:1119-8362