DOI: 10.4018/IJAEC.2018100102 International Journal of Applied Evolutionary Computation Volume 9 • Issue 4 • October-December 2018 Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 22 Solving Multi-Objective Multicast Routing Problem Using a New Hybrid Approach 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 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. KEywORdS Bat Algorithm, Chaotic Mapsfirefly Algorithm, Metaheuristics, Multi-Objective Optimization, Strength Pareto Evolutionary Algorithm 1. INTROdUCTION The problem of multi-objective optimization in a multicast routing involves the simultaneous optimization of several different and often competing objectives. In general, this problem does not admit a single optimal solution, but rather a set of alternative solutions, such as the comparison of these solutions is tricky because it is possible to find a better solution than another solution in relation to a given goal but not in all objectives of the problem. In this paper, the authors have proposed a new hybrid approach for multi-objective multicast routing (HMMA) that uses SPEA Algorithm to evaluate the solutions, and classified the population in two sets: the set of dominated solutions and the set of non-dominated solutions, the evolution of the dominated solutions is based on Bat Algorithm (BA), while the evolution of non-dominated solutions is based on Firefly Algorithm (FA), a process of replacing the older and the weaker solutions have been developed to enhance diversification. The rest of this article is organized as follows: section 2 illustrates various related work, section 3 presents, in general, the problems of multi-objective optimization, section 4 describes the problem studied, in section 5 the authors presented the different algorithms used in the proposed approach,