Master-Slave parallel genetic algorithm based on MapReduce using cloud computing

摘要：

　　The implementation platforms of parallel genetic algorithms (PGAs) include high performance computer,cluster and Grid.Contrast with the traditional platform,a Master-slave PGA based on MapReduce (MMRPGA) of cloud computing platform was proposed.Cloud computing is a new computer platform,suites for larger-scale computing and is low cost.At first,describes the design of MMRPGA,in which the whole evolution is controlled by Master and the fitness computing is assigned to Slaves; then deduces the theoretical speed-up of MMRPGA; at last,implements MMRPGA on Hadoop and compares the speed-up with traditional genetic algorithm,the experiment result shows MMRPGA can achieve slightly lower linearspeed-up with Mappers number.

关键词： Hadoop( )Master-slave PGA( )MapReduce( )parallelgenetic algorithms( )cloud computing

作者: LI Guang Ming ZENG Wen Hua ZHAO Jian Feng Liu Min

作者单位: Cognitive Science Department, Xiamen University, Xiamen, Fujian, China 361005;Software School of Xia Cognitive Science Department, Xiamen University, Xiamen, Fujian, China 361005;Fujian Key Laboratory

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4023-4027

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）