Evaluation of Sequential, Multi-objective, and Parallel Interactive Genetic Algorithms for Multi-objective Floor Plan Optimisation

  • Alexandra Melike Brintrup
  • Hideyuki Takagi
  • Jeremy Ramsden
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3907)


We propose a sequential IGA, multi-objective IGA and parallel interactive genetic algorithm (IGA), and evaluate them with a multi-objective floor planning task through both simulation and real IGA users. Combining human evaluation with an optimization system for engineering design enables us to embed domain specific knowledge which is frequently hard to describe, subjective criteria and preferences in engineering design. We introduce IGA technique to extend previous approaches with sequential single objective GA and multi-objective GA. We also introduce parallel IGA newly. Experimental results show that (1) the multi-objective IGA and the parallel IGA clearly provide better results than the sequential IGA, and (2) the multi-objective IGA provides more diverse results and faster convergence for a floor planning task although the parallel IGA provides better fitness convergence.


Pareto Front Parallel Genetic Algorithm Quantitative Fitness Interactive Genetic Algorithm Interactive Evolutionary Computation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alexandra Melike Brintrup
    • 1
  • Hideyuki Takagi
    • 2
  • Jeremy Ramsden
    • 1
  1. 1.School of Industrial and Manufacturing ScienceCranfield UniversityUK
  2. 2.Faculty of DesignKyushu UniversityFukuokaJapan

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