面向云制造的混流混合车间调度问题  

Cloud Manufacturing-oriented Mixed-model Hybrid Shop-scheduling Problem

作　　者：鲁建厦[1] 胡庆辉[1] 董巧英[1] 汤洪涛[1] 

机构地区：[1]浙江工业大学机械工程学院,杭州310014

出　　处：《中国机械工程》2017年第2期191-198,205,共9页China Mechanical Engineering

基　　金：浙江省自然科学基金资助项目(LY15G010009;LQ14E050004)

摘　　要：为解决云制造环境下混流混合车间的生产调度优化问题,综合考虑混流装配与零部件加工的集成优化以及外协云任务与自制任务的协同调度,建立了以最小化最大完工时间、均衡化零部件生产和最大化零件车间机器利用率为优化指标的多目标车间调度模型。基于零件分批和车间调度的两阶段求解策略,设计了一种两级递阶结构的混合生物地理学优化算法,采用在迁移算子中嵌入差分进化算法的变异策略来提高算法的搜索效率。最后,通过实例验证了模型和算法的有效性。To solve the scheduling problems for cloud manufacturing-oriented mixed-model hybrid shop, considering the integrated optimization of mixed flow assembly and part processing, and collab- orative scheduling of cloud service tasks and self-made tasks, the model was presented based on three objectives, minimizing the makespan, production smoothing of parts, and maximizing the utilization rate of the job shop. Then, a hybrid BBO algorithm with two level hierarchical structures was pro- posed to solve the model. In the hybrid algorithm, batching strategy was put forward in the first level and hybrid shop scheduling was designed in the second level. Moreover, a mutation strategy of differ- ential evolution algorithm was introduced to the transport operator of BBO to improve the searching efficiency. Finally, an example was given to test the model and algorithm, and the results demonstrat the feasibility and effectiveness of the method.

关 键 词：云制造 混流混合车间 混合生物地理学优化算法 零件分批 车间调度 

分 类 号：TB491[一般工业技术]