Quality of service routing strategy using supervised genetic algorithm

A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA...

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Main Authors: WANG, Zhaoxia, SUN, Yugeng, WANG, Zhiyong, SHEN, Huayu
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/5550
https://ink.library.smu.edu.sg/context/sis_research/article/6553/viewcontent/2007_QoS_Routing_Strategy_using_Supervised_Genetic_Algorithm__1_.pdf
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spelling sg-smu-ink.sis_research-65532021-01-07T14:28:44Z Quality of service routing strategy using supervised genetic algorithm WANG, Zhaoxia SUN, Yugeng WANG, Zhiyong SHEN, Huayu A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates the convergent process up to 20 times. 2007-02-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5550 https://ink.library.smu.edu.sg/context/sis_research/article/6553/viewcontent/2007_QoS_Routing_Strategy_using_Supervised_Genetic_Algorithm__1_.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University QoS routing Supervised genetic algorithm Supervised search rules Operations Research, Systems Engineering and Industrial Engineering Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic QoS routing
Supervised genetic algorithm
Supervised search rules
Operations Research, Systems Engineering and Industrial Engineering
Theory and Algorithms
spellingShingle QoS routing
Supervised genetic algorithm
Supervised search rules
Operations Research, Systems Engineering and Industrial Engineering
Theory and Algorithms
WANG, Zhaoxia
SUN, Yugeng
WANG, Zhiyong
SHEN, Huayu
Quality of service routing strategy using supervised genetic algorithm
description A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates the convergent process up to 20 times.
format text
author WANG, Zhaoxia
SUN, Yugeng
WANG, Zhiyong
SHEN, Huayu
author_facet WANG, Zhaoxia
SUN, Yugeng
WANG, Zhiyong
SHEN, Huayu
author_sort WANG, Zhaoxia
title Quality of service routing strategy using supervised genetic algorithm
title_short Quality of service routing strategy using supervised genetic algorithm
title_full Quality of service routing strategy using supervised genetic algorithm
title_fullStr Quality of service routing strategy using supervised genetic algorithm
title_full_unstemmed Quality of service routing strategy using supervised genetic algorithm
title_sort quality of service routing strategy using supervised genetic algorithm
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/5550
https://ink.library.smu.edu.sg/context/sis_research/article/6553/viewcontent/2007_QoS_Routing_Strategy_using_Supervised_Genetic_Algorithm__1_.pdf
_version_ 1770575506472697856