Abstract
Bandwidth-delay constrained least-cost multicast routing is a typical NP-complete problem. Although some swarm-based intelligent algorithms (e.g., genetic algorithm (GA)) are proposed to solve this problem, the shortcomings of local search affect the computational effectiveness. Taking the ability of building a robust network of Physarum network model (PN), a new hybrid algorithm, Physarum network-based genetic algorithm (named as PNGA), is proposed in this paper. In PNGA, an updating strategy based on PN is used for improving the crossover operator of traditional GA, in which the same parts of parent chromosomes are reserved and the new offspring by the \(Physarum\) network model is generated. In order to estimate the effectiveness of our proposed optimized strategy, some typical genetic algorithms and the proposed PNGA are compared for solving multicast routing. The experiments show that PNGA has more efficient than original GA. More importantly, the PNGA is more robustness that is very important for solving the multicast routing problem.
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Acknowledgments
This workThis work was supported by the National High Technology Research and Development Program of China (No. 2013AA013801), National Science and Technology Support Program (No. 2012BAD35B08), National Natural Science Foundation of China (Nos. 61402379, 61403315), and Natural Science Foundation Project of CQ CSTC (Nos. cstc2012jjA40013, cstc2013jcyjA40022).
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Liang, M., Gao, C., Liu, Y., Tao, L., Zhang, Z. (2015). A New Physarum Network Based Genetic Algorithm for Bandwidth-Delay Constrained Least-Cost Multicast Routing. In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9141. Springer, Cham. https://doi.org/10.1007/978-3-319-20472-7_29
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DOI: https://doi.org/10.1007/978-3-319-20472-7_29
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