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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/19913


    Title: 植基於Hadoop雲端運算架構之平行基因演算法與粒子群演算法的應用
    其他題名: The Application of Parallel Genetic Algorithm and Particle Swarm Optimization based on the Hadoop Cloud Computing Architecture
    Authors: 廖丞宇
    Liao, Chengyu
    指導教授: 游峰碩
    Yu, Feng Shuo
    Keywords: 雲端運算;平行基因演算法;粒子群演算法
    Cloud Computing;MapReduce;Hadoop;Parallel Genetic Algorithm;Particle Swarm Optimization
    Date: 2013
    Issue Date: 2013-10-08 15:36:11 (UTC+8)
    Abstract: 近年來,雲端運算為資訊科技領域中最熱門話題之一,而在眾多雲端技術中較為重要的便是Google所提出之MapReduce分散式運算框架。本研究提出MRPSO以及MRPGA兩種演算法,此二者分別整合了粒子群演算法(Particle Swarm Optimization)與MapReduce架構以及平行基因演算法(Parallel Genetic Algorithm)與MapReduce架構。MRPGA演算法經過數代演化後,藉由提供移民策略來增加族群的多樣性,並藉此提高演算法之求解效率。另一方面,PSO因可以視為是一種平行運算處理,再藉由結合HDFS檔案系統的輔助,MRPSO提供了更優質的尋解模式。本研究利用Hadoop平台,提出一個以MapReduce為基礎之平行基因演算法與粒子群演算法的設計實作,並將該演算法運用於派課問題的研究上。實驗結果證實本研究所設計之演算法的可行性,並且對於領域問題亦提供另一種解題模式。
    In recent year, Cloud Computing has become one of the hot topics in the area of information technology and among the various cloud technologies, the most important one is the MapReduce architecture proposed by Google. In this study, we propose MRPSO and MRPGA two algorithms that integrate the traditional PSO and Genetic Algorithm with the MapReduce architecture.In MRPGA, after several evolutions, some immigration strategy has been adopted to increase the diversity of population and to improve the efficient of computation. On the other hand, since PSO can be considered as parallel computation, therefore, with the help of HDFS file system, MRPSO provides a different architecture for searching solutions.In this study, we propose a design of parallel genetic algorithm and particle swarm optimization based on MapReduce computing architecture using Hadoop platform and we have tested our algorithm on the study of the Faculty-Course Assignment problem. The result shows the feasibility of our design which also provides another solution strategy for our domain problem.
    Appears in Collections:[資訊管理系所] 博碩士論文

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