Solving Multi-Objective Multicast Routing Problem Using a New Hybrid Approach

Mohammed Mahseur, Abdelmadjid Boukra and Yassine Meraihi
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Mohammed Mahseur: University of Sciences and Technology Houari Boumediene, Algeria
Abdelmadjid Boukra: University of Sciences and Technology Houari Boumediene, Algeria
Yassine Meraihi: University of M'Hamed Bougara Boumerdes, Algeria

International Journal of Applied Evolutionary Computation (IJAEC), 2018, vol. 9, issue 4, 22-36

Abstract: Multicast routing is the problem of finding the spanning tree of a set of destinations whose roots are the source node and its leaves are the set of destination nodes by optimizing a set of quality of service parameters and satisfying a set of transmission constraints. This article proposes a new hybrid multicast algorithm called Hybrid Multi-objective Multicast Algorithm (HMMA) based on the Strength Pareto Evolutionary Algorithm (SPEA) to evaluate and classify the population in dominated solutions and non-dominated solutions. Dominated solutions are evolved by the Bat Algorithm, and non-dominated solutions are evolved by the Firefly Algorithm. Old and weak solutions are replaced by new random solutions by a process of mutation. The simulation results demonstrate that the proposed algorithm is able to find good Pareto optimal solutions compared to other algorithms.

Date: 2018
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