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A Genetic Algorithm Optimization for Multi-Objective Multicast Routing

Ahmed Y. Hamed1, Monagi H. Alkinani2, M. R. Hassan3,*

1 Faculty of Computers and Information, Department of Computer Science, Sohag University, Sohag, 82524, Egypt
2 Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia
3 Faculty of Science, Department of Mathematics and Computer Science, Aswan University, Aswan, 81528, Egypt

* Corresponding Author: M. R. Hassan. Email:

Intelligent Automation & Soft Computing 2020, 26(6), 1201-1216.


Many applications require to send information from a source node to multiple destinations nodes. To support these applications, the paper presents a multi-objective based genetic algorithm, which is used in the construction of the multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weights (cost, delay, and hop) of the multicast tree. Experimental results prove that the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, the proposed approach has been applied to ten-node and twenty-node network to illustrate its efficiency. In addition, the execution time is reported for each studied case and the obtained results are compared with the results obtained by the previously based ant colony algorithm presented recently to solve the same problem. Finality, summing up the three objectives (cost, delay, and hop) to be one objective called the weight of the tree to speed up the searching process by using the proposed algorithm to find the best solutions.


Cite This Article

A. Y. Hamed, M. H. Alkinani and M. R. Hassan, "A genetic algorithm optimization for multi-objective multicast routing," Intelligent Automation & Soft Computing, vol. 26, no.6, pp. 1201–1216, 2020.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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