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Title page for etd-0815114-162246


URN etd-0815114-162246 Statistics This thesis had been viewed 1344 times. Download 379 times.
Author Hsuan-Hung Hsin
Author's Email Address No Public.
Department Computer Science and Enginerring
Year 2013 Semester 2
Degree Master Type of Document Master's Thesis
Language zh-TW.Big5 Chinese Page Count 41
Title A Hybrid Evolutionary Algorithm for Multi-Objective Optimization of Synthesis Gas Production
Keyword
  • Pareto front
  • Synthesis gas
  • multi-objective
  • Particle Swarm Optimization
  • Nelder-Mead simplex method
  • Nelder-Mead simplex method
  • Particle Swarm Optimization
  • multi-objective
  • Synthesis gas
  • Pareto front
  • Abstract A combined process of gas reforming is often used in chemical industry for different demands. In this work, hybridized Nelder-Mead simplex method and particle swarm optimization algorithm is employed to solve multi-objective problems. Some effects were expected by hybrid strengths and weaknesses of the two algorithms. The use of archive controller keeps each Pareto solution found during computing. By using the same measurement method, it was shown that hybrid evolutionary algorithm outperforms general evolutionary algorithms. In addition, the experimental results compared favorably with those found in the literature in terms of the degree of convergence and the dispersion of particles. This study demonstrates that the hybrid method is superior to PSO, and that the hybrid algorithm can effectively handle multi-objective optimization problems.
    Advisor Committee
  • Yi-Tung Kao - advisor
  • Files indicate access worldwide
    Date of Defense 2014-07-28 Date of Submission 2014-08-15


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