Using A Hybrid Algorithm to Improve the Quality of Services in Multicast Routing Problem
A Hybrid Learning automata-Genetic 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 and 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 NP-Complete 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.