An evolutionary, agent-assisted strategy for conceptual design space decomposition

  • I. C. Parmee
  • M. A. Beck
Novel Techniques and Applications of Evolutionary algorithms
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1305)


Genetic algorithm based strategies for the rapid decomposition of complex, conceptual design spaces into discrete, bounded regions of high performance are described The objective is not to identify single peaks but to identify high performance regions. Sufficient regional cover (in terns of number of solutions) is required for the extraction of infomnation relating to design characteristics to support the designer in decision making processes for the definition of optimal design direction. Three strategies using single population and parallel GA implemertations are described and results are presented An adaptive filter is introduced to eliminate a need for apron knowledge of the design space. Rule-based agents complement the search process by exploring identified regions to define region bounds.


Genetic Algorithm Design Space Adaptive Filter Design Sensitivity Parallel Genetic Algorithm 
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 Berlin Heidelberg 1997

Authors and Affiliations

  • I. C. Parmee
    • 1
  • M. A. Beck
    • 1
  1. 1.Plymouth Engineering Design CentreUniversity of PlymouthDrake Circus

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