摘要： 针对网格计算中的资源分配问题，提出一种融合粒子群优化算法和遗传算法的新算法。通过在粒子群算法中引入遗传算法，有效克服粒子群算法容易陷入局部最优值这一固有缺陷，重新在搜索空间寻找全局最优值。该方法具有操作简单、设置参数少、收敛速度快等特点。仿真实验结果表明，该融合算法在网格资源分配方面能取得较好的效果。

关键词: 网格计算, 资源分配, 粒子群优化算法

Abstract: This paper presents a new algorithm which integrates Particle Swarm Optimization(PSO) algorithm and Genetic Algorithm(GA) to solve the problem of resource allocation. According to the introduction of GA in the PSO algorithm, it effectively overcomes the inherent flaw of getting local optimal value by PSO algorithm and finds the global optimum value in the search space again. The method is simple, needs to set less parameters and speed up the convergence rate. Simulation results show the fusion algorithm achieves a better result in the aspect of grid resource allocation.

Key words: grid computing, resource allocation, Particle Swarm Optimization(PSO) algorithm

中图分类号: 

• TP311.52