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Modification in Genetic Algorithm

  • Kim F. Man
  • Kit S. Tang
  • Sam Kwong
  • Wolfgang A. Halang
Part of the Advances in Industrial Control book series (AIC)

Abstract

The GA mechanism is neither governed by the use of the differential equations nor does it behave like a continuous function. However, it possesses the unique ability to search and optimize a solution for a complex system, where other mathematical oriented techniques may have failed to compile the necessary design specifications. Due to its evolutionary characteristics, a standard GA may not be flexible enough for a practical application, and an engineering insight is always required whenever a GA is applied. This becomes more apparent where the problem to be tackled is complicated, multi-tasking and conflicting. Therefore, a means of modifying the GA structure is sought in order to meet the design requirements. There are many facets of operational modes that can be introduced. It is the main task of this chapter to outline the essential methodologies.

Keywords

Dynamic Time Warping Uniform Crossover Good Chromosome Chromosome Representation Minimum Spread 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 1997

Authors and Affiliations

  • Kim F. Man
    • 1
  • Kit S. Tang
    • 1
  • Sam Kwong
    • 2
  • Wolfgang A. Halang
    • 3
  1. 1.Electrical Engineering DepartmentCity University of Hong KongKowloonHong Kong
  2. 2.Computer Science DepartmentCity University of Hong KongKowloonHong Kong
  3. 3.Faculty of Electrical EngineeringFern UniversitatHagenGermany

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