With the rapid development of modern manufacturing industry, enterprises are required to have higher production efficiency and lower production energy consumption, resulting in more improvement of the automation degree of intelligent production workshop. This paper mainly studied green intelligent logistics scheduling of automated guided vehicle(AGV) in job shop. AGV logistics scheduling optimization model was establised to reduce the energy consumption of AGV and optimize AGV path. A genetic particle swarm optimization (PSO) algorithm was proposed with task sequencing as the constraint condition. Finally, the actual logistics scheduling of a knitting shop was taken as example to verify the method proposed in this paper. The calculation results show that the AGV logistics scheduling model proposed can well simulate the AGV green scheduling energy consumption, and the improved genetic particle swarm optimization algorithm presents a faster convergence speed and a better optimization ability.