基于SPSO的机械流水线负载任务分配方法  

Load Task Allocation Method of Mechanical Production Line Based on SPSO

作　　者：尚晓丽[1] 包向辉 

机构地区：[1]南京工业大学机械与动力学院,江苏南京210009

出　　处：《计算机仿真》2015年第2期423-427,共5页Computer Simulation

摘　　要：在弱通信条件下,传统的机械流水线任务分配方法采用任务的随机分配,无法根据流水线的实际负载能力,将应有的任务量分配到相应的流水线上。提出一种基于简化粒子群优化算法(Simplified particle swarm optimization algorithm,SPSO)的高效机械流水线任务分配方法,首先对每个流水线的实际负载能力进行动态评估。然后采用粒子群优化算法对所有流水线负载分配相应的计算任务。由于每个负载的任务量是根据实际的流水线性能来分配的,所以可以使得全局的效率最优化。最后通过实验对算法的性能进行验证。结果显示,改进方法在基于粒子群优化的机械流水线任务分配下,任务根据流水线性能,呈现很好的聚类,算法收敛性好,分配任务速度快,具有很好的应用价值。Under the condition of weak communication, the traditional task allocation methods of mechanical pro- duction line use random way to allocate tasks, which cannot allocate some of tasks to the corresponding production line according to the actual load capacity of production line. An efficient task allocation method of mechanical pro- duction line based on simplified particle swarm optimization algorithm （SPSO） was proposed in the paper. First of all, the actual load capacity of each production line was dynamically evaluated, based on this, the particle swarm op- timization algorithm was adopted to allocate corresponding computing tasks to all the production line＇s load. Since each task load was allocated according to the actual performance of production line, it can make the optimized effi- ciency of global. Finally, experiments were used to validate the performance of the algorithm. The results show that based on particle swarm optimization for task allocation of mechanical production line, the improved method show good clustering according to the performance of production line, and the algorithm has good convergence, fast task al- location and great application value.

关 键 词：机械流水线 任务分配 粒子群优化算法 弱通信 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]