随机机器故障下加工时间可控的并行机鲁棒调度

Robust Scheduling of Unrelated Parallel Machines Subject to Stochastic Breakdowns and Controllable Processing Times

现实生产环境中经常面临随机机器故障,造成初始调度方案性能恶化。针对并行机环境下工件加工时间可控,提出内外两层嵌套式的鲁棒调度策略,旨在降低随机机器故障造成的成本损失期望,干扰发生后通过局部修复实现跟初始计划的匹配。内层建立非线性0-1混合整数规划模型,通过二次锥化方法来求解初始调度方案在随机机器故障干扰情景下的成本损失期望。外层设计基于工件柔性和机器不可用概率的排序算法;由于问题内在的复杂性,利用遗传算法优化工件柔性参数,进而增强初始调度方案的鲁棒性。最后设计随机仿真实验,分别验证了在机器故障所造成的单位时间扰动成本不同时和机器维修水平不同时所提鲁棒调度策略的有效性。

Inevitable machine breakdowns always degrade the performance of the initial schedule in the practice.Considering the controllable processing time in unrelated parallel machines layout,how to generate a robust schedule to reduce the expectation value of the loss cost caused by the stochastic machine failures is studied.Therefore,a robust scheduling strategy of two nested layers is designed.In the inner layer,a nonlinear 0-1mixed integer model is built to calculate the expectation of the loss cost.Because of the model's complexity,it is translated into second-order cone constrains for solving efficiency.In the outer layer,sorting algorithm is designed based on the job's flexibility and the probability of machine unavailability.Due to inherent complex and unstructured nature,genetic algorithm is used to optimize job's flexible parameters,and to further enhance the robustness of the initial schedule.Through randomly generated numerical experiments,It shows that the proposed scheduling strategy is robust against different disturbance cost per unit time and different mean time to repair of machine breakdown.The research has a certain reference for sorting robust schedule and optimizing job's flexible parameters.