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A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing

Liang, Mingxin, Gao, Chao and Zhang, Zili 2017, A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing, Natural computing, vol. 16, no. 1, pp. 85-98, doi: 10.1007/s11047-016-9545-6.

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Title A new genetic algorithm based on modified Physarum network model for bandwidth-delay constrained least-cost multicast routing
Author(s) Liang, Mingxin
Gao, Chao
Zhang, Zili
Journal name Natural computing
Volume number 16
Issue number 1
Start page 85
End page 98
Total pages 14
Publisher Springer
Place of publication Dodrecht, The Netherlands
Publication date 2017-03
ISSN 1567-7818
1572-9796
Keyword(s) multicast routing
genetic algorithm
Physarum network model
Summary A mobile ad hoc network is a kind of popular self-configuring network, in which multicast routing under the quality of service constraints, is a significant challenge. Many researchers have proved that such problem can be formulated as a NP-complete problem and proposed some swarm-based intelligent algorithms to solve the optimal solution, such as the genetic algorithm (GA), bees algorithm. However, a lower efficiency of local search ability and weak robustness still limit the computational effectiveness. Aiming to those shortcomings, a new hybrid algorithm inspired by the self-organization of Physarum, is proposed in this paper. In our algorithm, an updating scheme based on Physarum network model (PM) is used for improving the crossover operator of traditional GAs, in which the same parts of parent chromosomes are reserved and the new offspring by the PM is generated. In order to estimate the effectiveness of our proposed optimized scheme, some typical genetic algorithms and their updating algorithms (PMGAs) are compared for solving the multicast routing on four different datasets. The simulation experiments show that PMGAs are more efficient than original GAs. More importantly, the PMGAs are more robustness that is very important for solving the multicast routing problem. Moreover, a series of parameter analyses is used to find a set of better setting for realizing the maximal efficiency of our algorithm.
Language eng
DOI 10.1007/s11047-016-9545-6
Field of Research 080503 Networking and Communications
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30085246

Document type: Journal Article
Collection: School of Information Technology
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