Abstract: The problem of multi-objective flexible job shop scheduling optimization of batch production is studied, where multi-objects of makespan, earliness/tardiness, production cost and equipment utilization rate (total and maximum machine tool loads) are concerned. The strategy of job shop scheduling opti-mization of batch production is proposed. The model of multi-objective scheduling optimization is set up. Aiming at improving searching efficiency and searching quality, multiple population hybrid algorithm combining both advantages of particle swarm optimization and genetic algorithm is presented. A simulation experiment is carried out to illustrate that the pro-posed model and algorithm is more efficiency and feasible than that used in home and abroad in existence at present. Finally, from the fact of production, a example of multi-objective flexi-ble job shop scheduling optimization in batch production is addressed. The experimental results can play a definite part in directing production.

Key words: Batch production, Evolutionary algorithm, Flexible job shop scheduling, Multi-objective optimization