柔性作业车间动态调度问题研究

为了有效求解柔性作业车间动态调度问题,提出了一个基于多目标免疫遗传算法(MOIGA)的动态调度优化算法。首先定义了柔性作业车间动态调度问题,然后采用事件驱动和周期驱动相结合的调度策略,提出了基于MOIGA的动态调度优化模型,接着设计了面向交货期性能最优的柔性作业车间调度算法,并讨论了影响算法复杂度的因素,最后通过一个实例仿真,表明了算法的可行性和优越性。

Research on Flexible Job Shop Dynamic Scheduling Problem

A multi-objective immune genetic algorithm (MOIGA) based dynamic scheduling optimization algorithm was proposed to solve the flexible job shop dynamic scheduling problem. The problem was defined in which deviation degree criterion was proposed with the delivery date criterion to reflect the difference between the pre-scheduling and the rescheduling. A MOIGA-based interactive optimization model integrating periodic and event-driven dynamic scheduling strategy was proposed. An operation-extended based encoding way was put forward and a bidirectional scheduling algorithm aiming at the earliness/tardiness (E/T) criteria optimized was proposed in the decoding step. The factors related with MOIGA's time complexity was discussed. A simulation example result shows that the optimization model can solve the problem effectively and efficiently.