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dc.contributor.authorYang, Shengxiangen
dc.contributor.authorCheng, Huien
dc.contributor.authorWang, Fangen
dc.identifier.citationYang, S., Cheng, H. and Wang, F. (2010) Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 40(1), January 2010, pp. 52-63.en
dc.description.abstractIn recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent new-generation wireless networks. The experimental results show that these immigrants and memory-based GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce high-quality solutions after each change.en
dc.subjectDynamic optimization problem (DOP)en
dc.subjectDynamic shortest path routing problem (DSPRP)en
dc.subjectGenetic algorithmen
dc.subjectImmigrants schemeen
dc.subjectMemory schemeen
dc.subjectMobile ad hoc network (MANET)en
dc.titleGenetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks.en
dc.researchgroupCentre for Computational Intelligenceen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en

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