基于动态粒子群优化的网格任务调度算法

摘要

提出了一种基于动态粒子群优化的网格任务调度算法.设计了网格任务调度问题的数学模型,给出了自适应变异的动态粒子群优化算法的框架,引入了自适应学习因子和自适应变异策略,从而使算法具有动态自适应性,能够较容易地跳出局部最优.实验结果表明,本算法能有效地解决异构网格任务调度问题,具有较好的应用价值.%This paper proposed a novel grid task scheduling solution based on dynamic particle swarm optimization algorithm.Expounded the mathematical model of grid task scheduling problem, gave the framework of dynamic particle swarm optimization algorithm, introducod the adaptive learning factors and the adaptive mutation strategy to make proposed algorithm easily jump out of local optimum with effective dynamic adaptability.Experimental result shows that the proposed algorithm can solve the scheduling problem of heterogeneous grid meta-task, and has the advantage of good application value.