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Parallelizing Modified Cuckoo Search on MapReduce Architecture
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作者 Chia-Yu Lin yuan-ming pai +2 位作者 Kun-Hung Tsai Charles H.-P. Wen Li-Chun Wang 《Journal of Electronic Science and Technology》 CAS 2013年第2期115-123,共9页
Meta-heuristics typically takes long time to search optimality from huge amounts of data samples for applications like communication, medicine, and civil engineering. Therefore, parallelizing meta-heuristics to massiv... Meta-heuristics typically takes long time to search optimality from huge amounts of data samples for applications like communication, medicine, and civil engineering. Therefore, parallelizing meta-heuristics to massively reduce runtime is one hot topic in related research. In this paper, we propose a MapReduce modified cuckoo search (MRMCS), an efficient modified cuckoo search (MCS) implementation on a MapReduce architecture--Hadoop. MapReduce particle swarm optimization (MRPSO) from a previous work is also implemented for comparison. Four evaluation functions and two engineering design problems are used to conduct experiments. As a result, MRMCS shows better convergence in obtaining optimality than MRPSO with two to four times speed-up. 展开更多
关键词 Index Terms-Cuckoo search MAPREDUCE META-HEURISTICS particle swarm optimization.
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