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    The cross-entropy method in multi-objective optimisation: An assessment

    Access Status
    Fulltext not available
    Authors
    Bekker, J.
    Aldrich, Chris
    Date
    2011
    Type
    Journal Article
    
    Metadata
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    Citation
    Bekker, James and Aldrich, Chris. 2011. The cross-entropy method in multi-objective optimisation: An assessment. European Journal of Operational Research. 211 (1): pp. 112-121.
    Source Title
    European Journal of Operational Research
    DOI
    10.1016/j.ejor.2010.10.028
    ISSN
    0377-2217
    School
    WASM Minerals Engineering and Extractive Metallurgy Teaching Area
    URI
    http://hdl.handle.net/20.500.11937/18384
    Collection
    • Curtin Research Publications
    Abstract

    Solving multi-objective problems requires the evaluation of two or more conflicting objective functions, which often demands a high amount of computational power. This demand increases rapidly when estimating values for objective functions of dynamic, stochastic problems, since a number of observations are needed for each evaluation set, of which there could be many. Computer simulation applications of real-world optimisations often suffer due to this phenomenon. Evolutionary algorithms are often applied to multi-objective problems. In this article, the cross-entropy method is proposed as an alternative, since it has been proven to converge quickly in the case of single-objective optimisation problems. We adapted the basic cross-entropy method for multi-objective optimisation and applied the proposed algorithm to known test problems. This was followed by an application to a dynamic, stochastic problem where a computer simulation model provides the objective function set. The results show that acceptable results can be obtained while doing relatively few evaluations.

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