Title page for etd-0718116-154924


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URN etd-0718116-154924
Author Yuan-ching Peng
Author's Email Address No Public.
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Department Department of Computer Science and Engineering
Year 2015
Semester 2
Degree Master
Type of Document
Language English
Title Design of Multi-population Genetic Algorithms under Different Hierarchical Architectures
Date of Defense 2016-07-13
Page Count 89
Keyword
  • Genetic algorithm
  • multiple sub-populations
  • migration strategy
  • hierarchical execution structure
  • meta-heuristic
  • Abstract Metaheuristics have recently been commonly used to solve complex problems in real applications. They are easy to use and usually get good solutions for the problems. There were many approaches proposed in improving the performance of the metaheuristics. Some scholars also used multiple populations in meta-heuristic approaches to shorten the generation number needed to find nearly optimal solutions. In this thesis, we revisit the multi-population mechanisms and design several hierarchical execution architectures of GA. We make three main parts of contribution in this thesis. In the first part, we review the properties of sub-population execution for GA, and design a hierarchical sub-population architecture. In the second part, we embed different migration mechanisms in the above hierarchical sub-population architecture and compare their performance. In the third part of the thesis, we further consider adding aliens to merged sub-populations to increase diversity and reserve elitists. Experiments are also made for verifying the effectiveness and efficiency of the proposed approaches. From the experimental results, it is found that the hierarchical sub-population architecture could easily avoid solutions trapped in local optima, the migration mechanism could make solution quality of sub-populations better, and adding aliens could increase search variety.
    Advisory Committee
  • Wen-yang Lin - chair
  • Ming-chao Chiang - co-chair
  • Chun-Hao Chen - co-chair
  • Tzung-Pei Hong - advisor
  • Files
  • etd-0718116-154924.pdf
  • Indicate in-campus at 3 year and off-campus access at 3 year.
    Date of Submission 2016-08-22

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