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Workshops on Applications of Evolutionary Computation

EvoWorkshops 2006: Applications of Evolutionary Computing pp 586–598Cite as

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

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 3907)

Abstract

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.

Keywords

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

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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  • DOI: 10.1007/11732242_56
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Author information

Authors and Affiliations

  1. School of Industrial and Manufacturing Science, Cranfield University, Bedfordshire, MK43 0AL, UK

    Alexandra Melike Brintrup & Jeremy Ramsden

  2. Faculty of Design, Kyushu University, 4-9-1, Shiobaru, Minami-ku, Fukuoka, 815-8540, Japan

    Hideyuki Takagi

Authors
  1. Alexandra Melike Brintrup
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  2. Hideyuki Takagi
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  3. Jeremy Ramsden
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Editor information

Editors and Affiliations

  1. Johannes Gutenberg University, Mainz, Germany

    Franz Rothlauf

  2. Institute AIFB, University of Karlsruhe, 76128, Karlsruhe, Germany

    Jürgen Branke

  3. Dipartimento di Ingegneria dell’Informazione, Università di Parma,  

    Stefano Cagnoni

  4. Centre of Informatics and Systems of the University of Coimbra,  

    Ernesto Costa

  5. Dept. LCC, Universidad de Málaga, Spain

    Carlos Cotta

  6. Institute of Computer Science, University of Bremen, 28359, Bremen, Germany

    Rolf Drechsler

  7. INRIA Saclay - Ile-de-France, Parc Orsay Université, 4, rue Jacques Monod, 91893, ORSAY Cedex, France

    Evelyne Lutton

  8. CISUC, Department of Informatics Engineering, University of Coimbra, Polo II of the University of Coimbra, 3030, Coimbra, Portugal

    Penousal Machado

  9. Dartmouth College, Lebanon, NH, USA

    Jason H. Moore

  10. Universidade de A Coruña, CP 15071, A Coruña, Spain

    Juan Romero

  11. School of Computing Sciences, UEA Norwich, University of East Anglia, NR4 7TJ, Norwich, UK

    George D. Smith

  12. Dipartimento di Automatica e Informatica, Politecnico di Torino, Italy

    Giovanni Squillero

  13. Kyushu University, Japan

    Hideyuki Takagi

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© 2006 Springer-Verlag Berlin Heidelberg

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Brintrup, A.M., Takagi, H., Ramsden, J. (2006). Evaluation of Sequential, Multi-objective, and Parallel Interactive Genetic Algorithms for Multi-objective Floor Plan Optimisation. In: , et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_56

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  • DOI: https://doi.org/10.1007/11732242_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33237-4

  • Online ISBN: 978-3-540-33238-1

  • eBook Packages: Computer ScienceComputer Science (R0)