International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume4,August 2017,

Topic : An Improved Genetic Algorithm in C for Knapsack Problem

Authors:Manpreet Kaur ||

Abstract:Genetic Algorithms (GA) provide a simple method to solve complex optimization problems. The performance of a Genetic Algorithm mainly depends on the genetic parameters, operators and the fitness function used. This paper proposed an improved Genetic Algorithm to solve a NP-hard problem i.e. Knapsack problem. The Improved GA is implemented using C programming language. It gives better results when compared against an existing GA to solve the Knapsack Problem. This paper also proposes an optimal parameter setting for Knapsack Problem using GA..

Keywords: Genetic Algorithm (GA), Knapsack Problem (KP), crossover, mutation, premature convergence, fitness function, Elitism.

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DOI: 01.1617/vol4/iss8/pid80976


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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