Statistics seminar:: SELC : Sequential Elimination of Level Combinations by Means of Modified Genetic Algorithms

Event Details
  • Date/Time:
    • Thursday April 22, 2004
      12:00 pm - 12:00 am
  • Location: 228 ISyE main building
  • Phone:
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  • Fee(s):
    N/A
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Contact
Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher
404.385.3102
Summaries

Summary Sentence: Statistics seminar:: SELC : Sequential Elimination of Level Combinations by Means of Modified Genetic Algorithms

Full Summary: Statistics seminar:: SELC : Sequential Elimination of Level Combinations by Means of Modified Genetic Algorithms

To search for an optimal design in a large search space, Wu, Mao, Ma
(1990) suggested the SEL-method to find an optimal setting. Genetic
algorithms (GA) can be used to improve upon this method. To make the
search procedure more efficient, new ideas of forbidden array and weighted
mutation are introduced. Relaxing the condition of orthogonality, GA is
able to accommodate a variety of design points which allows more
flexibility and enhances the chance of getting the best setting in fewer
runs, particularly in the presence of interactions. The search procedure
is enriched by a Bayesian method for identifying the important main
effects and two-factor interactions. Illustration is given with the
optimization of three functions, one of which is from Shekel's family.

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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Status
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:39am
  • Last Updated: Oct 7, 2016 - 9:52pm