Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding an optimal deadlock-free schedules in a manufacturing system with very limited buffer is presented. This algorithm ...Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding an optimal deadlock-free schedules in a manufacturing system with very limited buffer is presented. This algorithm is based on the effective genetic algorithm (GA) search method, and a formal Petri net structure is introduced to detect the token player assuring deadlock-free. In order to make the scheduling strategy generated by GA meet the required constraint of deadlock-free, some results of the structure analysis of Petri net are involved as a criterion to select deadlock-free schedule from the population generated by GA. The effectiveness and efficiency of the proposed approach is illustrated by using an example.展开更多
针对传统蚁群算法在农机导航路径规划中存在前期搜索盲目、死锁、收敛速度慢、收敛路径质量低的问题,本文提出基于跳点优化蚁群算法(Jump point optimized ant colony algorithm,JPOACO)的路径规划方法。首先,使用优化跳点搜索算法对地...针对传统蚁群算法在农机导航路径规划中存在前期搜索盲目、死锁、收敛速度慢、收敛路径质量低的问题,本文提出基于跳点优化蚁群算法(Jump point optimized ant colony algorithm,JPOACO)的路径规划方法。首先,使用优化跳点搜索算法对地图进行预处理,获得简化跳点;其次,通过简化跳点对栅格地图进行信息素初始化,以加强简化跳点的引导能力和减少前期盲目搜索;接着,设计蚂蚁死亡惩罚机制,以降低陷入死锁蚂蚁走过路径的信息素,减少死锁问题的发生;再者,通过重新设计启发式信息函数并引入分级式信息素因子改进状态转移概率函数,以提高收敛速度,缩短路径长度;最后,采用路径优化策略删减不必要路径节点,以进一步缩短路径长度、提升平滑度,提高路径质量。仿真结果表明,在简单环境中,JPOACO算法求得的路径长度较传统蚁群算法和另一种优化蚁群算法短约22.6%和2.0%,收敛迭代次数、收敛时间分别减少约77.0%、77.5%和49.3%、87.8%,零死亡迭代次数和零死亡时间较后者减少约19.5%和80.5%;在复杂菠萝种植环境中,JPOACO算法较传统蚁群算法和另一种优化蚁群算法求得的路径长度短16.6%和4.7%,收敛迭代次数、收敛时间分别减少约77.1%、17.4%和73.7%、47.4%,零死亡迭代次数和零死亡时间较后者减少约34.3%和58.2%,表明本文算法具有较高的适用性和可行性。展开更多
为实现自动小车存取系统的实时控制,基于双重着色赋时Petri网(Colored Ti med Petri Nets,CTPN)构建了RGVs系统(Rail-Guided Vehicles system,RGVs)的动态模型。同时为了提高RGVs系统的存储效率,对RGV小车采用基于最短路径的调度策略。...为实现自动小车存取系统的实时控制,基于双重着色赋时Petri网(Colored Ti med Petri Nets,CTPN)构建了RGVs系统(Rail-Guided Vehicles system,RGVs)的动态模型。同时为了提高RGVs系统的存储效率,对RGV小车采用基于最短路径的调度策略。并针对RGVs系统的临界状态即将发生环路(环路链)死锁的状况,提出了一种死锁预防的方法。最后基于VC.NET验证其有效性。展开更多
基金This project was supported by the National Natural Science Foundation of China (60074011, 70071017).
文摘Deadlock must be avoided in a manufacturing system. In this paper, an efficient algorithm for finding an optimal deadlock-free schedules in a manufacturing system with very limited buffer is presented. This algorithm is based on the effective genetic algorithm (GA) search method, and a formal Petri net structure is introduced to detect the token player assuring deadlock-free. In order to make the scheduling strategy generated by GA meet the required constraint of deadlock-free, some results of the structure analysis of Petri net are involved as a criterion to select deadlock-free schedule from the population generated by GA. The effectiveness and efficiency of the proposed approach is illustrated by using an example.
文摘针对传统蚁群算法在农机导航路径规划中存在前期搜索盲目、死锁、收敛速度慢、收敛路径质量低的问题,本文提出基于跳点优化蚁群算法(Jump point optimized ant colony algorithm,JPOACO)的路径规划方法。首先,使用优化跳点搜索算法对地图进行预处理,获得简化跳点;其次,通过简化跳点对栅格地图进行信息素初始化,以加强简化跳点的引导能力和减少前期盲目搜索;接着,设计蚂蚁死亡惩罚机制,以降低陷入死锁蚂蚁走过路径的信息素,减少死锁问题的发生;再者,通过重新设计启发式信息函数并引入分级式信息素因子改进状态转移概率函数,以提高收敛速度,缩短路径长度;最后,采用路径优化策略删减不必要路径节点,以进一步缩短路径长度、提升平滑度,提高路径质量。仿真结果表明,在简单环境中,JPOACO算法求得的路径长度较传统蚁群算法和另一种优化蚁群算法短约22.6%和2.0%,收敛迭代次数、收敛时间分别减少约77.0%、77.5%和49.3%、87.8%,零死亡迭代次数和零死亡时间较后者减少约19.5%和80.5%;在复杂菠萝种植环境中,JPOACO算法较传统蚁群算法和另一种优化蚁群算法求得的路径长度短16.6%和4.7%,收敛迭代次数、收敛时间分别减少约77.1%、17.4%和73.7%、47.4%,零死亡迭代次数和零死亡时间较后者减少约34.3%和58.2%,表明本文算法具有较高的适用性和可行性。
文摘为实现自动小车存取系统的实时控制,基于双重着色赋时Petri网(Colored Ti med Petri Nets,CTPN)构建了RGVs系统(Rail-Guided Vehicles system,RGVs)的动态模型。同时为了提高RGVs系统的存储效率,对RGV小车采用基于最短路径的调度策略。并针对RGVs系统的临界状态即将发生环路(环路链)死锁的状况,提出了一种死锁预防的方法。最后基于VC.NET验证其有效性。
