DocumentCode :
2558322
Title :
K- shortest path network problem solution with a hybrid Genetic Algorithm: Particle Swarm Optimization algorithm
Author :
Kusetogullari, H. ; Leeson, M.S. ; Ren, W. ; Hines, E.L.
Author_Institution :
Sch. of Eng., Univ. of Warwick, Coventry, UK
fYear :
2011
fDate :
26-30 June 2011
Firstpage :
1
Lastpage :
4
Abstract :
This paper presents a hybrid evolutionary algorithm (HGAPSO) to maximize utilization and improve the Quality of Service (QoS) in expanding networks. Two meta-heuristic optimization algorithms, namely a Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are combined to find the feasible solution within a search space of telecommunication networks. By employing a local search based priority encoding method, each individual in the GA and each particle in PSO is represented as a potential solution for the routing problem. The performance of HGAPSO is compared to both the GA and PSO alone for finding the K-shortest paths, demonstrating its superiority.
Keywords :
genetic algorithms; particle swarm optimisation; quality of service; telecommunication network routing; HGAPSO; K- shortest path network problem solution; hybrid evolutionary algorithm; hybrid genetic algorithm; meta heuristic optimization algorithms; particle swarm optimization algorithm; priority encoding method; quality of service; routing problem; telecommunication networks; Algorithm design and analysis; Biological cells; Genetic algorithms; Optimization; Particle swarm optimization; Quality of service; Routing; Genetic Algorithm; Hybrid algorithm; K-shortest path; Particle Swarm Optimization; network routing; utilization of Quality of Service;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Transparent Optical Networks (ICTON), 2011 13th International Conference on
Conference_Location :
Stockholm
ISSN :
2161-2056
Print_ISBN :
978-1-4577-0881-7
Electronic_ISBN :
2161-2056
Type :
conf
DOI :
10.1109/ICTON.2011.5970873
Filename :
5970873
Link To Document :
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