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Finding multi-constrained path using genetic algorithm

To properly support networked multimedia applications, it is important for the network to provide quality-of-service (QoS) guarantees. One way to provide QoS guarantees is for the network to perform QoS routing, where the path taken must fulfill certain constraints. Multi-constrained path (MCP) prob...

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Main Authors:	Yussof S., See O.H.
Other Authors:	16023225600
Format:	Conference paper
Published:	2023
Subjects:	Genetic algorithm Multi-constrained path QoS routing Algorithms Bioelectric phenomena Diesel engines Food additives Genetic algorithms Heuristic programming Image storage tubes Nuclear propulsion Quality of service Telecommunication systems Exact algorithms Genetic Algorithm (GA) High probability International conferences Malaysia Multimedia applications NP-Complete One way QoS guarantees Approximation algorithms
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id	my.uniten.dspace-29757
record_format	dspace
spelling	my.uniten.dspace-297572023-12-28T16:57:34Z Finding multi-constrained path using genetic algorithm Yussof S. See O.H. 16023225600 16023044400 Genetic algorithm Multi-constrained path QoS routing Algorithms Bioelectric phenomena Diesel engines Food additives Genetic algorithms Heuristic programming Image storage tubes Nuclear propulsion Quality of service Telecommunication systems Exact algorithms Genetic algorithm Genetic Algorithm (GA) High probability International conferences Malaysia Multi-constrained path Multimedia applications NP-Complete One way QoS guarantees QoS routing Approximation algorithms To properly support networked multimedia applications, it is important for the network to provide quality-of-service (QoS) guarantees. One way to provide QoS guarantees is for the network to perform QoS routing, where the path taken must fulfill certain constraints. Multi-constrained path (MCP) problem refers to the problem of finding a path through a network subject to multiple additive constraints. It has been proven that this problem is NP-complete and therefore no exact algorithm can be found. As such, various heuristics and approximation algorithms have been proposed to solve the MCP problem. This paper presents a solution to the MCP problem using genetic algorithm (GA). Through simulation, this algorithm has been shown to give a high probability of finding a feasible path if such paths exist. �2007 IEEE. Final 2023-12-28T08:57:34Z 2023-12-28T08:57:34Z 2007 Conference paper 10.1109/ICTMICC.2007.4448579 2-s2.0-48349139409 https://www.scopus.com/inward/record.uri?eid=2-s2.0-48349139409&doi=10.1109%2fICTMICC.2007.4448579&partnerID=40&md5=645eb116880b3b93668d16d08ddc2966 https://irepository.uniten.edu.my/handle/123456789/29757 4448579 713 718 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	Genetic algorithm Multi-constrained path QoS routing Algorithms Bioelectric phenomena Diesel engines Food additives Genetic algorithms Heuristic programming Image storage tubes Nuclear propulsion Quality of service Telecommunication systems Exact algorithms Genetic algorithm Genetic Algorithm (GA) High probability International conferences Malaysia Multi-constrained path Multimedia applications NP-Complete One way QoS guarantees QoS routing Approximation algorithms
spellingShingle	Genetic algorithm Multi-constrained path QoS routing Algorithms Bioelectric phenomena Diesel engines Food additives Genetic algorithms Heuristic programming Image storage tubes Nuclear propulsion Quality of service Telecommunication systems Exact algorithms Genetic algorithm Genetic Algorithm (GA) High probability International conferences Malaysia Multi-constrained path Multimedia applications NP-Complete One way QoS guarantees QoS routing Approximation algorithms Yussof S. See O.H. Finding multi-constrained path using genetic algorithm
description	To properly support networked multimedia applications, it is important for the network to provide quality-of-service (QoS) guarantees. One way to provide QoS guarantees is for the network to perform QoS routing, where the path taken must fulfill certain constraints. Multi-constrained path (MCP) problem refers to the problem of finding a path through a network subject to multiple additive constraints. It has been proven that this problem is NP-complete and therefore no exact algorithm can be found. As such, various heuristics and approximation algorithms have been proposed to solve the MCP problem. This paper presents a solution to the MCP problem using genetic algorithm (GA). Through simulation, this algorithm has been shown to give a high probability of finding a feasible path if such paths exist. �2007 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	Finding multi-constrained path using genetic algorithm
title_short	Finding multi-constrained path using genetic algorithm
title_full	Finding multi-constrained path using genetic algorithm
title_fullStr	Finding multi-constrained path using genetic algorithm
title_full_unstemmed	Finding multi-constrained path using genetic algorithm
title_sort	finding multi-constrained path using genetic algorithm
publishDate	2023
_version_	1806427965503832064
score	13.222552

Finding multi-constrained path using genetic algorithm

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