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DC Field | Value | Language |
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dc.contributor.author | Cheng, H | - |
dc.contributor.author | Yang, S | - |
dc.date.accessioned | 2011-09-19T15:34:35Z | - |
dc.date.available | 2011-09-19T15:34:35Z | - |
dc.date.issued | 2009 | - |
dc.identifier.citation | IEEE Congress on Evolutionary Computation (CEC 2009), Trondheim: 3135 - 3140, 2009-05-18 - 2009-05-21 | en_US |
dc.identifier.isbn | 978-1-4244-2958-5 | - |
dc.identifier.other | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4983340 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/5826 | - |
dc.description | This article is posted here with permission from the IEEE - Copyright @ 2009 IEEE | en_US |
dc.description.abstract | In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks (ANNs), genetic algorithms (GAs), particle swarm optimization (PSO), etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless sensor network (WSN), etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem (DOP) in MANETs. In this paper, we propose to use elitism-based immigrants GA (EIGA) to solve the dynamic SP problem in MANETs. We consider MANETs as target systems because they represent new generation wireless networks. The experimental results show that the EIGA can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change. | en_US |
dc.description.sponsorship | This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1. | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | ad hoc networks | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Mobile computing | en_US |
dc.subject | Telecommunication network topology | en_US |
dc.title | Genetic algorithms with elitism-based immigrants for dynamic shortest path problem in mobile ad hoc networks | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1109/CEC.2009.4983340 | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel (Active) | - |
pubs.organisational-data | /Brunel/Brunel (Active)/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Research Centres (RG) | - |
pubs.organisational-data | /Brunel/Research Centres (RG)/CIKM | - |
pubs.organisational-data | /Brunel/School of Information Systems, Computing and Mathematics (RG) | - |
pubs.organisational-data | /Brunel/School of Information Systems, Computing and Mathematics (RG)/CIKM | - |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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