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An Intelligent Expert Systems' Approach to Layout Decision Analysis and Design under Uncertainty

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Intelligent Decision Making: An AI-Based Approach

Part of the book series: Studies in Computational Intelligence ((SCI,volume 97))

This chapter describes an intelligent soft computing based approach to layout decision analysis and design. The solution methodology involves the use of heuristics, metaheuristics, human intuition as well as soft computing tools like artificial neural networks, fuzzy logic, and expert systems. The research framework and prototype contribute to the field of intelligent decision making in layout analysis and design by enabling explicit representation of experts' knowledge, formal modeling of fuzzy user preferences, and swift generation/manipulation of superior layout alternatives to facilitate the cognitive, ergonomic, and economic efficiency of layout designers.

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Author information

Authors and Affiliations

  1. Systems Design Engineering, University of Waterloo, Canada

    Abdul-Rahim Ahmad & Otman Basir

  2. School of Business, McMaster University, Canada

    Khaled Hassanein

  3. Environmental Systems Engineering, University of Regina, Canada

    Shahid Azam

Authors
  1. Abdul-Rahim Ahmad
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  2. Otman Basir
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  3. Khaled Hassanein
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  4. Shahid Azam
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Editor information

Editors and Affiliations

  1. Loyola College in Maryland, 4501 N. Charles Street, 21210, Baltimore, MD, USA

    Gloria Phillips-Wren

  2. University of South Australia, SA 5095, Adelaide, Australia

    Nikhil Ichalkaranje  & Lakhmi C. Jain  & 

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Ahmad, AR., Basir, O., Hassanein, K., Azam, S. (2008). An Intelligent Expert Systems' Approach to Layout Decision Analysis and Design under Uncertainty. In: Phillips-Wren, G., Ichalkaranje, N., Jain, L.C. (eds) Intelligent Decision Making: An AI-Based Approach. Studies in Computational Intelligence, vol 97. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76829-6_12

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  • DOI: https://doi.org/10.1007/978-3-540-76829-6_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76828-9

  • Online ISBN: 978-3-540-76829-6

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