Design optimization is an important engineering design activity. Performing design optimization in the presence of uncertainty has been an active area of research. The approaches used require modeling the random variables using precise probability distributions or representing uncertain quantities as fuzzy sets. This work, however, considers problems in which the random variables are described with imprecise probability distributions, which are highly relevant when there is limited information about the distribution of a random variable. In particular, this paper formulates the imprecise probability design optimization problem and presents an approach for solving it. We present examples for illustrating the approach.


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    Title :

    Design Optimization with Imprecise Random Variables


    Additional title:

    Sae Int. J. Mater. Manf
    Sae International Journal of Materials and Manufacturing


    Contributors:

    Conference:

    SAE World Congress & Exhibition ; 2009



    Publication date :

    2009-04-20


    Size :

    9 pages




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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