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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
Bioline Code: ja16070
Full paper language: English
Document type: Research Article
Document available free of charge

Journal of Applied Sciences and Environmental Management, Vol. 20, No. 3, 2016, pp. 593-596

 en 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 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

Genetic Algorithm; Crossover; Heuristic; Arithmetic; Intermediate; Evolutionary Algorithm

© Copyright 2016 - Journal of Applied Sciences and Environmental Management

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