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    Improved orthogonal array based simulated annealing for design optimization

    134800_134800.pdf (248.7Kb)
    Access Status
    Open access
    Authors
    Chan, Kit Yan
    Kwong, C.
    Lua, X.
    Date
    2009
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Chan, Kit and Kwong, Che and Lua, X. 2009. Improved orthogonal array based simulated annealing for design optimization. Expert Systems with Applications. 36 (4): pp. 7379-7389.
    Source Title
    Expert Systems with Applications
    DOI
    10.1016/j.eswa.2008.09.022
    ISSN
    09574174
    Faculty
    Curtin Business School
    The Digital Ecosystems and Business Intelligence Institute (DEBII)
    School
    Digital Ecosystems and Business Intelligence Institute (DEBII)
    Remarks

    The link to the journal’s home page is: http://www.elsevier.com/wps/find/journaldescription.cws_home/939/description#description. Copyright © 2009 Elsevier B.V. All rights reserved

    URI
    http://hdl.handle.net/20.500.11937/40213
    Collection
    • Curtin Research Publications
    Abstract

    Recent research shows that simulated annealing with orthogonal array based neighbourhood functions can help in the search for a solution to a parametrical problem which is closer to an optimum when compared with conventional simulated annealing. Previous studies of simulated annealing analyzed only the main effects of variables of parametrical problems. In fact, both main effects of variables and interactions between variables should be considered, since interactions between variables exist in many parametrical problems. In this paper, an improved orthogonal array based neighbourhood function (IONF) for simulated annealing with the consideration of interaction effects between variables is described. After solving a set of parametrical benchmark function problems where interaction effects between variables exist, results of the benchmark tests show that the proposed simulated annealing algorithm with the IONF outperforms significantly both the simulated annealing algorithms with the existing orthogonal array based neighbourhood functions and the standard neighbourhood functions. Finally, the improved orthogonal array based simulated annealing was applied on the optimization of emulsified dynamite packing-machine design by which the applicability of the algorithm in real world problems can be evaluated and its effectiveness can be further validated.

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