Aiming at dynamic vehicle scheduling problem that is dynamic vehicle routing problem（ DVRP） with vehicle capacity constraints in real time existed in process of logistics distribution

self-adaptive quantum genetic algorithm（ SAQGA） is proposed to minimize the distribution cost. According to change rate of search point target functions

a new update mode adaptive quantum rotation gate is presented

and direction and magnitude of the quantum rotating angle is determined by changes in fitness values of sub-propulation

thus evolutionary direction of population is guided to improve depth of global search of algorithm. A mutation operation is designed to keep the population diversity of the self-adaptive quantum genetic algorithm and width of the global search of algorithm is improved. To enhance the local optimization ability

local search method based on the principle of two elements search is introduced. Simulation experiments and algorithm comparisons demonstrate the effectiveness and the superiority of the proposed algorithm.