A new optimization algorithm is presented, which is based on the genetic algorithm (GA) and quantumbehaved particle swarm optimization (QPSO) algorithm. The algorithm uses the crossover and mutation operators of GA to optimize the QPSO algorithm, improves its global search ability and overcomes the disadvantage that QPSO algorithm easily falls into local extremum. It is used to extract the character of the Pseudo-Voigt-shaped Brillouin scattering spectrum. The parameters estimation and simulation analysis of Brillouin scattering spectrum are analyzed under different weight ratios, line widths and signal-to-noise ratios. The experimental data of Brillouin scattering spectrum are collected in different temperatures and processed by GA-QPSO algorithm.The experimental results show that the GA-QPSO algorithm can improve the frequency shift extraction accuracy of Brillouin scattering spectrum. The maximum error of frequency shift fitting is 2.18 MHz under 25 ℃ and the average fitting error decreases with the increase of temperature, gradually.The frequency shift fitting maximum error is 0.065 MHz under 80 ℃. Therefore, the new algorithm can be used for measuring the temperature and strain in Brillouin scattering sensing system. It has a very good application prospect in improving spatial resolution and detection precision.