Title of article :
Comparative Analysis of Genetic Crossover Operators in Knapsack Problem
Author/Authors :
hakimi, d federal university of technology - department of mathematics, Nigeria , oyewola, do federal university of technology - department of mathematics, Nigeria , yahaya, y federal university of technology - department of mathematics, Nigeria , bolarin, g federal university of technology - department of mathematics, Nigeria
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.
Keywords :
Genetic Algorithm , Crossover , Heuristic , Arithmetic , Intermediate , Evolutionary Algorithm
Journal title :
Journal of Applied Sciences and Environmental Management
Journal title :
Journal of Applied Sciences and Environmental Management
