Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1695
Title: Comparative Analysis of Genetic Crossover Operators in Knapsack Problem
Authors: Hakimi, Danladi
Oyewola, David O.
Yahaya, Yusuph
Bolarin, Gbolahan
Keywords: Genetic Algorithms
Issue Date: Sep-2016
Publisher: Journal of Applied Sciences and Environmental Management
Citation: Hakimi, D., Oyewola, D.O.,Yahaya, Y. and Bolarin, G. (2016), Comparative Analysis of Genetic Crossover Operators in Knapsack Problem, J. Appl. Sci. Environ. Management, Vol. 20 (3) 593-596, http://dx.doi.org/10.4314/jasem.v20i3.13
Abstract: 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.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/1695
ISSN: 1119-8362
Appears in Collections:Mathematics

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