基于双仲裁机制和田口正交法的猫群优化任务调度算法

针对异构计算系统任务调度过程中通信冲突以及算法运行时间的问题，该文提出一种基于双仲裁机制和田口正交法的猫群优化任务调度算法。首先利用双仲裁机制对任务资源进行管理，动态判决任务的分配，有效避免通信冲突，再将田口正交法应用到猫群优化过程的跟踪模式中，降低算法运行时间，提高解的质量。实验结果表明，该算法运行速度明显高于其他算法至少约10%，算法在处理大量任务时的并行化效果最优，在异构环境中也体现出其相当大的优势。

Cat Swarm Optimization Task Scheduling Algorithm Based on Double Arbitration Mechanism and Taguchi Orthogonal Method

To solve communication conflicts and algorithm running time problem in task scheduling process of heterogeneous computing system, a cat swarm optimization task scheduling algorithm is proposed based on double arbitration mechanism and Taguchi orthogonal method. Firstly, the double arbitration mechanism is used to manage the task resources, and the task assignment is dynamically decided to avoid effectively communication conflicts. Then, the Taguchi orthogonal method is applied to the tracking mode of the cat swarm optimization process to reduce the algorithm running time and improve the quality of the solution. Experimental results show that the algorithm runs at a rate of at least about 10% faster than other algorithms. The algorithm performs best in parallelism when dealing with a large number of tasks and has considerable advantages in heterogeneous environments.