A parallel multi-families genetic algorithm (PMOGA) is proposed to reduce computing burden which is incurred in the solution of the multi-objective optimization problem in chemical process when combining the single genetic algorithm (GA) with the process simulator.A master-slave node distributed computing strategy is employed in the proposed algorithm.Based on the idea of decomposition-coordination

the Pareto curve is divided into multi-sections

and then the calculation task of each sub-section is assigned to single computer in LAN to reduce the computing time.The proposed method has been tested on two practical chemical examples.The results show that PMOGA is superior to single GA in both uniformity and comprehensiveness of the Pareto solutions.