S^4R(systems of sequential systems with shared resources)网是分析和解决柔性制造系统死锁现象常用的一种重要的Petri网子类模型,现有的基于S^4R网的死锁预防方法通常采用对部分或者全部严格极小信标添加控制库所来实现.此类方法的...S^4R(systems of sequential systems with shared resources)网是分析和解决柔性制造系统死锁现象常用的一种重要的Petri网子类模型,现有的基于S^4R网的死锁预防方法通常采用对部分或者全部严格极小信标添加控制库所来实现.此类方法的不足在于得到的活性S^4R控制器中往往存在冗余控制库所.针对已为网中每一个严格极小信标都逐一添加了控制库所和相关连接弧的活性S^4R控制器,本文提出并设计了一种基于整数规划技术的冗余检测及结构简化方法,由此得到结构更简单、行为允许度更高的活性S^4R控制器.该方法的核心思想是:如果网中已经存在一个P-不变式使得某个严格极小信标满足最大受控条件,那么为该严格极小信标添加的控制库所就是冗余的.由于该方法无需进行Petri网的可达性分析,避免了状态组合爆炸问题,因此具有较高的可行性和计算效率.最后用实验验证了本文方法的正确性和有效性.展开更多
Due to the complexity of dynamic job shop scheduling in flexible manufacturing system(FMS), many heuristic rules are still used today. A dynamic scheduling approach based on Lagrangian relaxation is proposed to improv...Due to the complexity of dynamic job shop scheduling in flexible manufacturing system(FMS), many heuristic rules are still used today. A dynamic scheduling approach based on Lagrangian relaxation is proposed to improve the quality and guarantee the real time capability of dynamic scheduling. The proposed method makes use of the dynamic predictive optimal theory combined with Lagrangian relaxation to obtain a good solution that can be evaluated quantitatively. The Lagrangian multipliers introduced here are capable of describing machine predictive states and system capacity constraints. This approach can evaluate the suboptimality of the scheduling systems. It can also quickly obtain high quality feasible schedules, thus enabling Lagrangian relaxation to be better used in the dynamic scheduling of manufacturing system. The efficiency and effectiveness of this method are verified by numerical experiments. 展开更多
文摘S^4R(systems of sequential systems with shared resources)网是分析和解决柔性制造系统死锁现象常用的一种重要的Petri网子类模型,现有的基于S^4R网的死锁预防方法通常采用对部分或者全部严格极小信标添加控制库所来实现.此类方法的不足在于得到的活性S^4R控制器中往往存在冗余控制库所.针对已为网中每一个严格极小信标都逐一添加了控制库所和相关连接弧的活性S^4R控制器,本文提出并设计了一种基于整数规划技术的冗余检测及结构简化方法,由此得到结构更简单、行为允许度更高的活性S^4R控制器.该方法的核心思想是:如果网中已经存在一个P-不变式使得某个严格极小信标满足最大受控条件,那么为该严格极小信标添加的控制库所就是冗余的.由于该方法无需进行Petri网的可达性分析,避免了状态组合爆炸问题,因此具有较高的可行性和计算效率.最后用实验验证了本文方法的正确性和有效性.
文摘Due to the complexity of dynamic job shop scheduling in flexible manufacturing system(FMS), many heuristic rules are still used today. A dynamic scheduling approach based on Lagrangian relaxation is proposed to improve the quality and guarantee the real time capability of dynamic scheduling. The proposed method makes use of the dynamic predictive optimal theory combined with Lagrangian relaxation to obtain a good solution that can be evaluated quantitatively. The Lagrangian multipliers introduced here are capable of describing machine predictive states and system capacity constraints. This approach can evaluate the suboptimality of the scheduling systems. It can also quickly obtain high quality feasible schedules, thus enabling Lagrangian relaxation to be better used in the dynamic scheduling of manufacturing system. The efficiency and effectiveness of this method are verified by numerical experiments.
