Extraction of Emerging Multi-Objective Design Information from COGA Data

  • J. A. R Abraham
  • I. C. Parmee


The paper describes further developments of the interactive evolutionary design concept relating to the emergence of mutually inclusive regions of high performance solutions relating to differing objectives from cluster-oriented genetic algorithm (COGAs) output. These common regions are further defined by the application of clustering algorithms and relevant variable analysis. The multi-objective output of the COGA is then compared to output from a strength Pareto evolutionary algorithm (SPEA-II).


Pareto Front Information Gain Objective Space Adaptive Filter Pareto Frontier 
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 2004

Authors and Affiliations

  • J. A. R Abraham
    • 1
  • I. C. Parmee
    • 1
  1. 1.Advanced Computation in Design and Decision-making (ACDDM)University of the West of EnglandBristol

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