An Artificial Fish Swarm Algorithm for the Multicast Routing Problem

Qing LIU  Tomohiro ODAKA  Jousuke KUROIWA  Haruhiko SHIRAI  Hisakazu OGURA  

IEICE TRANSACTIONS on Communications   Vol.E97-B   No.5   pp.996-1011
Publication Date: 2014/05/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E97.B.996
Type of Manuscript: PAPER
Category: Network
artificial fish swarm algorithm,  multicast routing,  Steiner tree problem,  network optimization,  

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This paper presents an artificial fish swarm algorithm (AFSA) to solve the multicast routing problem, which is abstracted as a Steiner tree problem in graphs. AFSA adopts a 0-1 encoding scheme to represent the artificial fish (AF), which are then subgraphs in the original graph. For evaluating each AF individual, we decode the subgraph into a Steiner tree. Based on the adopted representation of the AF, we design three AF behaviors: randomly moving, preying, and following. These behaviors are organized by a strategy that guides AF individuals to perform certain behaviors according to certain conditions and circumstances. In order to investigate the performance of our algorithm, we implement exhaustive simulation experiments. The results from the experiments indicate that the proposed algorithm outperforms other intelligence algorithms and can obtain the least-cost multicast routing tree in most cases.