文献类型：会议论文

英文题名：The Application of An Improved Cultural Algorithm in Grid Computing

作者：Zhou Wei[1];Bu Yan-ping[2];Zhou Ye-qing[3]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Shanghai Jiao Tong Univ, Sch Technol, Shanghai 201101, Peoples R China;[3]Fudan Univ, Sch Math Sci, Shanghai 200433, Peoples R China

会议论文集：25th Chinese Control and Decision Conference (CCDC)

会议日期：MAY 25-27, 2013

会议地点：Guiyang, PEOPLES R CHINA

语种：英文

外文关键词：cultural algorithm; particle swarm optimization algorithm; grid; task scheduling

摘要：A cultural algorithm, rooting from simulation of evolution of human being society, provides a new computable framework of evolution algorithms. A novel cultural algorithm based on particle swarm optimization (PSO) algorithm was proposed in this paper. With the advent of the grid, task scheduling in heterogeneous environments becomes more and more important. After analyzing the model of grid scheduling problem, the CPSO algorithm was presented to solve the resource scheduling problem in grid computing. The optimal objective is to minimize the total completing time. The improved algorithm can keep all the advantages of the standard PSO, such as implementation simplicity, low computational burden, and few control parameters, etc. Simulation results demonstrate that it can be superior to the regular PSO. We also tested the CPSO algorithm with the Max-Min method to show the algorithm's efficiency.