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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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 |
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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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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 |
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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 |
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13.250246 |