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The effect of GA parameters on the performance of GA-based QoS routing algorithm

Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. However, the performance of GA depends largely on the values chosen for the GA parameters. In the previous work, a GA-based QoS routing algorithm for solving the multicons...

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Main Authors: Yussof S., See O.H.
Other Authors: 16023225600
Format: Conference paper
Published: 2023
Subjects:
Diesel engines
Genetic algorithms
Information technology
Network routing
Population statistics
Multiconstrained path problems
Mutation probabilities
Natural selections
Optimization algorithms
Population sizes
QoS routing algorithms
Simulation results
Routing algorithms
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id my.uniten.dspace-30877
record_format dspace
spelling my.uniten.dspace-308772023-12-29T15:55:09Z The effect of GA parameters on the performance of GA-based QoS routing algorithm Yussof S. See O.H. 16023225600 16023044400 Diesel engines Genetic algorithms Information technology Network routing Population statistics Multiconstrained path problems Mutation probabilities Natural selections Optimization algorithms Population sizes QoS routing algorithms Simulation results Routing algorithms Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. However, the performance of GA depends largely on the values chosen for the GA parameters. In the previous work, a GA-based QoS routing algorithm for solving the multiconstrained path (MCP) problem has been developed. This paper presents the simulation result of the effect of three GA parameters which are maximum iterations, population size and mutation probability on the developed algorithm. � 2008 IEEE. Final 2023-12-29T07:55:09Z 2023-12-29T07:55:09Z 2008 Conference paper 10.1109/ITSIM.2008.4631912 2-s2.0-57349179990 https://www.scopus.com/inward/record.uri?eid=2-s2.0-57349179990&doi=10.1109%2fITSIM.2008.4631912&partnerID=40&md5=177b5c68c62ee8047aa8c0c5319234f9 https://irepository.uniten.edu.my/handle/123456789/30877 3 4631912 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Diesel engines
Genetic algorithms
Information technology
Network routing
Population statistics
Multiconstrained path problems
Mutation probabilities
Natural selections
Optimization algorithms
Population sizes
QoS routing algorithms
Simulation results
Routing algorithms
spellingShingle Diesel engines
Genetic algorithms
Information technology
Network routing
Population statistics
Multiconstrained path problems
Mutation probabilities
Natural selections
Optimization algorithms
Population sizes
QoS routing algorithms
Simulation results
Routing algorithms
Yussof S.
See O.H.
The effect of GA parameters on the performance of GA-based QoS routing algorithm
description Genetic algorithm (GA) is a powerful search and optimization algorithm inspired by the theory of genetics and natural selection. However, the performance of GA depends largely on the values chosen for the GA parameters. In the previous work, a GA-based QoS routing algorithm for solving the multiconstrained path (MCP) problem has been developed. This paper presents the simulation result of the effect of three GA parameters which are maximum iterations, population size and mutation probability on the developed algorithm. � 2008 IEEE.
author2 16023225600
author_facet 16023225600
Yussof S.
See O.H.
format Conference paper
author Yussof S.
See O.H.
author_sort Yussof S.
title The effect of GA parameters on the performance of GA-based QoS routing algorithm
title_short The effect of GA parameters on the performance of GA-based QoS routing algorithm
title_full The effect of GA parameters on the performance of GA-based QoS routing algorithm
title_fullStr The effect of GA parameters on the performance of GA-based QoS routing algorithm
title_full_unstemmed The effect of GA parameters on the performance of GA-based QoS routing algorithm
title_sort effect of ga parameters on the performance of ga-based qos routing algorithm
publishDate 2023
_version_ 1806423331347365888
score 13.214268

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