基于关键路径链和PACGA的网络总线资源调度方法研究

针对传统工业控制网络总线资源调度算法在节点数量逐渐增加时收敛速度慢和搜索精度不高,且准确度及效率低等问题, 提出了一种基于关键路径链和多态蚁群遗传算法(PACGA)的资源调度方法,采用关键路径链的调度算法获取需求调度的节点,不同节点间采用多态蚁群遗传算法进行资源的调度,依据照工业控制网络资源调度的特征,用自适应调整挥发系数增强节点的全局搜索性能,通过候选节点集方法缩小搜索区域提高算法的搜索效率,完成工业控制网络总线资源的高效调度。仿真实验说明,该种方法在工业控制过程中任务数量较多的情况下仍然具备较高的运行效率和精度,并且具有较低的运行时间,具有较强的应用价值。

Based on critical path chain and PACGA network bus resource scheduling method research

For traditional bus industrial control network resource scheduling algorithm in the number of nodes increase gradually slow convergence speed and searching precision is not high, and low accuracy and efficiency, this paper proposes a chain based on the critical path and polymorphic ant colony genetic algorithm (PACGA) resource scheduling method, using the critical path of chain scheduling algorithm for scheduling of node demand, between different nodes using polymorphic ant colony genetic algorithm for resource scheduling, according to according to the characteristics of the industrial control network resources scheduling, with the adaptive adjustment of volatile coefficient strengthen the global search capability of the nodes, through the candidate node set method to reduce the search area improve the searching efficiency of the algorithm, complete highly bus industrial control network resources scheduling. Simulation experiment shows that the method in the process of industrial control task number of cases still have higher efficiency and precision, and has lower running time, with strong application value.