With the rapid development of science and technology, China’s modern manufacturing technology has developed and progressed rapidly, and the degree of automation of intelligent production workshops has gradually increased. Enterprises are facing huge challenges in path optimization and energy conservation and emission reduction. This paper mainly studies the problem of AGV green intelligent logistics scheduling in textile workshops. First, an AGV logistics scheduling optimization model with the goal of reducing AGV energy consumption and optimal AGV path is established, and then an improved genetic particle swarm optimization algorithm with task sequencing as the constraint is proposed. Take the actual scheduling data of a textile workshop as an example to verify the method in this paper. From the calculation results, the AGV logistics scheduling model proposed in this paper can better simulate the energy consumption problem of AGV green scheduling. The improved genetic particle swarm algorithm proposed has a better optimization ability and a faster speed in solving such problems. Speed of convergence.