摘要
网格任务分配是一个NP难问题,结合微粒群优化(Particle Swarm Optimization,PSO)算法,和网格自身的特性,提出了基于网格的混合微粒群算法。算法对问题的解空间进行变换、重定义,使之更加符合PSO算法的求解环境,实现了网格资源的优化分配。与离散微粒群(DPSO)算法和遗传算法进行了仿真比较,结果表明,新的PSO算法具有较好的性能。
Grid task allocation is a typical NP complete problem. According to the essence of grid and based on Particle Swarm Optimization algorithm, this paper proposes a new algorithm called Grid-based Hybrid Particle Swarm Optimization（GHPSO）. This algorithm transforms and redefines the problem＇ s resolution space to make it more suitable to the problem-solving enviromrtent of PSO algorithm, achieves the optimal allocation of grid resources. The simulation results compared with the Discrete Particle Swarm Optimization algorithm and Genetic Algorithm show that this algorithm has better performance.
出处
《计算机工程与应用》
CSCD
2012年第12期34-37,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.60803027)
关键词
网格任务分配
微粒群优化算法
解空间变换
grid task scheduling
Grid-based Hybrid Particle Swarm Optimization （GHPSO）
problem＇ s resolutionspace transformation
