Abstract The model of optimizing multi-objective flow shop scheduling with stochastic processing time and machine breakdown is analyzed. The multi-objective flow shop scheduling problem is modeled with the stochastic processing time and machine breakdown. A mathematical scheme is designed for the solutions with the longest flow time or the longest delay time. A hybrid multi-objective genetic algorithm is proposed to solve the optimization problems iteratively in uncertain condition. The simulation results show that the proposed algorithm has good performance for the flow shop scheduling problems in uncertain condition.
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2009, Vol. 22 
