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Journal of Applied Sciences and Environmental Management
World Bank assisted National Agricultural Research Project (NARP) - University of Port Harcourt
ISSN: 1119-8362
Vol. 20, No. 3, 2016, pp. 593-596
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Bioline Code: ja16070
Full paper language: English
Document type: Research Article
Document available free of charge
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Journal of Applied Sciences and Environmental Management, Vol. 20, No. 3, 2016, pp. 593-596
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Comparative Analysis of Genetic Crossover Operators in Knapsack Problem
HAKIMI, D.; OYEWOLA, D.O.; YAHAYA, Y. & BOLARIN, G.
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. © JASEM
Keywords
Genetic Algorithm; Crossover; Heuristic; Arithmetic; Intermediate; Evolutionary Algorithm
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© Copyright 2016 - Journal of Applied Sciences and Environmental Management
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