Solving multiobjective multicast routing problem with a new ant colony optimization approach

Authors:
Diego Pinto;Benjamín Barán
Affiliations:
National University of Asunción and Catholic University of Asunción, Paraguay;National University of Asunción and Catholic University of Asunción, Paraguay
Venue:
LANC '05 Proceedings of the 3rd international IFIP/ACM Latin American conference on Networking
Year:
2005

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Abstract

This work presents two multiobjective algorithms for Multicast Traffic Engineering. The proposed algorithms are new versions of the Multi-Objective Ant Colony System (MOACS) and the Max-Min Ant System (MMAS), based on Ant Colony Optimization (ACO). Both ACO algorithms simultaneously optimize maximum link utilization and cost of a multicast routing tree, as well as average delay and maximum end-to-end delay, for the first time using an ACO approach. In this way, a set of optimal solutions, know as Pareto set is calculated in only one run of the algorithms, without a priori restrictions. Experimental results show a promising performance of both proposed algorithms for a multicast traffic engineering optimization, when compared to a recently published Multiobjective Multicast Algorithm (MMA), specially designed for Multiobjective Multicast Routing Problems.