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In order to solve the problem that symbiotic organisms search algorithm converge slowly and easy to fall into the local optimum, combining quantum genetic algorithm theory, this paper proposed a real-coded quantum symbiotic organisms search algorithm( RQSOS). First, this paper presented the concept of the difference degree based on the principle of triangular fuzzy number, and constructed a variable component vector and a pair of probability amplitude of a allele in a chromosome that could carry more information and enhance the diversity of the solutions. Then it proposed the mode of rotary learning based on the Archimedes spiral, which strengthened the exploration ability of the solution space. Finally it updated the difference degree based on SOS, and carried out the population learning and mutation operations based on the value of the difference degree which could make the whole population evolution rapidly towards the optimal direction and reduced the probability of falling into local optimum. It was verified by numerical optimization and cloud task scheduling problem, and the simulation results show that the RQSOS algorithm can significantly improve the convergence speed and optimization ability, which is a feasible and effective algorithm. [ABSTRACT FROM AUTHOR]