Abstract
Aiming at the problems that the traditional gravitational search algorithm is easy to fall into local optimum and the diversity of particles is insufficient. An improved gravitational search algorithm (IGSA) is proposed to increase the diversity of particles and the selected optimal particles by adding crossover operators and using Metropolis criterion. Considering the different demands of business types and network performance, a suitable fitness function is constructed with technique for order preference by similarity to an ideal solution (TOPSIS) and grey relational analysis (GRA). The weights of the evaluation indices for network selection are obtained by solving the fitness function with IGSA. According to quality of service (QoS) requirements of different business types, compared with the traditional gravitational search algorithm (GSA), particle swarm optimization algorithm (PSO) and genetic algorithm (GA), the simulation results indicate that the IGSA can find a network with higher fitness and better meet different QoS.
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