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An integrated approach to automated innovization for discovering useful design principles: Case studies from engineering
Michigan State University. (BEACON Center for the Study of Evolution in Action)
University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Engineering Science. (Simulation-based optimization)
Universidad de Las Palmas de Gran Canaria. (Institute of Intelligent Systems and Numerical Applications in Engineering)
University of Minho, Campus de Azurém. (Institute for Polymer and Composites – I3N)
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2014 (English)In: Applied Soft Computing, ISSN 1568-4946, E-ISSN 1872-9681, Vol. 15, no 2, 42-56 p.Article in journal (Refereed) Published
Abstract [en]

Computational optimization methods are most often used to find a single or multiple optimal or near-optimal solutions to the underlying optimization problem describing the problem at hand. In this paper, we elevate the use of optimization to a higher level in arriving at useful problem knowledge associated with the optimal or near-optimal solutions to a problem. In the proposed innovization process, first a set of trade-off optimal or near-optimal solutions are found using an evolutionary algorithm. Thereafter, the trade-off solutions are analyzed to decipher useful relationships among problem entities automatically so as to provide a better understanding of the problem to a designer or a practitioner. We provide an integrated algorithm for the innovization process and demonstrate the usefulness of the procedure to three real-world engineering design problems. New and innovative design principles obtained in each case should clearly motivate engineers and practitioners for its further application to more complex problems and its further development as a more efficient data analysis procedure.

Place, publisher, year, edition, pages
Elsevier, 2014. Vol. 15, no 2, 42-56 p.
Keyword [en]
Multi-objective optimization, Innovization, Design principles, Extrusion process, Noise barrier optimization, Friction stir welding
National Category
Mechanical Engineering Computer Science
Research subject
URN: urn:nbn:se:his:diva-9978DOI: 10.1016/j.asoc.2013.10.011ISI: 000329457400004ScopusID: 2-s2.0-84888631059OAI: diva2:748242
Available from: 2014-09-18 Created: 2014-09-18 Last updated: 2016-02-22Bibliographically approved

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Bandaru, Sunith
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