CHEN Yong，ZHENG Xin-fan，Wang Ya-liang，LU Jian-sha
（Key Laboratory of Special Purpose Equipment and Advanced Processing Technology，Ministry of Education，
Zhejiang University of Technology，Hangzhou 310014，China）
Abstract：Aiming at the Job-Shop scheduling problem under uncertainties and dynamic disruption events，a new Job-Shop schedulingmodel was set up，which based on fuzzy number theory and dynamic scheduling strategy and considering of the makespan，manufacturingcost of machines and machine load. To get the optimization，genetic simulated annealing algorithm was designed and improved. The initialscheduling scheme was gotten through simulation，and on this basisuncertaindisturbanceeventswasstudiedbydynamicscheduling
strategy. Empirical researching of production workshop in an electric products company was done. The better scheduling soheme wasgotten，the machine utilization and customer satisfaction was effectively improved. The results indicate that the model and algorithm arefeasibility and can be well used into real workshop.
Key words：Job-Shop；genetic algorithm simulated annealing（GASA）；uncertainties；scheduling