Multiobjective Max-Min Ant System. An application to Multicast Traffic Engineering

نویسندگان

  • Diego Pinto
  • Benjamín Barán
چکیده

Ant Colony Optimization (ACO) has been already established as a practical approach to solve single-objective combinatorial problems. This work proposes a new approach for the resolutions of Multi-Objective Problems (MOPs) inspired in Max-Min Ant System (MMAS). To probe our new approach, a multicast traffic-engineering problem was solved using the proposed approach as well as a Multiobjective Multicast Algorithm (MMA), a multi-objective evolutionary algorithm (MOEA) specially designed for that multicast problem. Experimental results show the advantages of the new approach over MMA considering the quantity and quality of calculated solutions.

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تاریخ انتشار 2005