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Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in mobile ad hoc networks

  • Hui Cheng
    ,
  • Shengxiang Yang
    ,
  • Fang Wang
Research Output:
Contribution to journal
Article
 Peer-review

Abstract

In 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.

Publication Information

Output type

Research Output:
Contribution to journal
Article
 Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 52-63

Journal (Volume, Issue Number)

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews (Volume 40, Issue 1)

Publication milestones

  • Published - 01/01/2010

Publication status

Published - 01/01/2010

Publication IDs

  • handle.net: 10547/224175
  • Scopus: 73049087609

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