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In this thesis, the author described a new genetic algorithm based on the idea: the better design could be found at the neighbor of the current best design. The details

In this thesis, the author described a new genetic algorithm based on the idea: the better design could be found at the neighbor of the current best design. The details of the new genetic algorithm are described, including the rebuilding process from Micro-genetic algorithm and the different crossover and mutation formation.

Some popular examples, including two variable function optimization and simple truss models are used to test this algorithm. In these study, the new genetic algorithm is proved able to find the optimized results like other algorithms.

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    Date Created
    • 2015
    Resource Type
  • Text
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    Note
    • Partial requirement for: M.S., Arizona State University, 2015
      Note type
      thesis
    • Includes bibliographical references (p. 44-46)
      Note type
      bibliography
    • Field of study: Civil and environmental engineering

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    by Xiaosu Ding

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