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
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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 13.214268