Automatic guided vehicle (AGV) has become an important transportation tool in job shop, which brings new problems for job shop scheduling, such as AGV assigned, AGV power constraint, AGV quantity constraint and so on. Aiming to green scheduling problem of job shop considering AGVs charging, the multi-objective job shop scheduling optimization model with makespan and energy consumption was established considering the AGV power and AGV charging, and the improved genetic algorithm is devised to solve this model. In the algorithm, the two-segment chromosome coding of equal length job assignment and AGV allocation was using, the local search strategy and corresponding GA operators for job and AGV code segment were adopted, the decoding mechanism considering AGV power and charging constraints was designed. Finally, through the orthogonal experimental simulation of ft06 case using the method of range and variance, the influence of AGV quantity and AGV power on the optimization was analyzed. The model and algorithm were verified by simulation.