Mohammad Reza Karami Nejad
Using A Hybrid Algorithm to Improve the Quality of Services in Multicast Routing Problem
1256 - 1261
2012
6
10
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/13763
https://publications.waset.org/vol/70
World Academy of Science, Engineering and Technology
A hybrid learning automatagenetic algorithm (HLGA) is proposed to solve QoS routing optimization problem of next generation networks. The algorithm complements the advantages of the learning Automato Algorithm(LA) and Genetic Algorithm(GA). It firstly uses the good global search capability of LA to generate initial population needed by GA, then it uses GA to improve the Quality of Service(QoS) and acquiring the optimization tree through new algorithms for crossover and mutation operators which are an NPComplete problem. In the proposed algorithm, the connectivity matrix of edges is used for genotype representation. Some novel heuristics are also proposed for mutation, crossover, and creation of random individuals. We evaluate the performance and efficiency of the proposed HLGAbased algorithm in comparison with other existing heuristic and GAbased algorithms by the result of simulation. Simulation results demonstrate that this paper proposed algorithm not only has the fast calculating speed and high accuracy but also can improve the efficiency in Next Generation Networks QoS routing. The proposed algorithm has overcome all of the previous algorithms in the literature.
Open Science Index 70, 2012