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    An exact penalty function method for nonlinear mixed discrete programming problems

    Access Status
    Fulltext not available
    Authors
    Changjun, Y.
    Teo, Kok Lay
    Bai, Y.
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Changjun, Yu and Teo, Kok Lay and Bai, Yanqin. 2013. An exact penalty function method for nonlinear mixed discrete programming problems. Optimization Letters. 7 (1): pp. 23-38.
    Source Title
    Optimization Letters
    DOI
    10.1007/s11590-011-0391-2
    ISSN
    18624472
    URI
    http://hdl.handle.net/20.500.11937/39347
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we consider a general class of nonlinear mixed discrete programming problems. By introducing continuous variables to replace the discrete variables, the problem is first transformed into an equivalent nonlinear continuous optimization problem subject to original constraints and additional linear and quadratic constraints. Then, an exact penalty function is employed to construct a sequence of unconstrained optimization problems, each of which can be solved effectively by unconstrained optimization techniques, such as conjugate gradient or quasi-Newton methods. It is shown that any local optimal solution of the unconstrained optimization problem is a local optimal solution of the transformed nonlinear constrained continuous optimization problem when the penalty parameter is sufficiently large. Numerical experiments are carried out to test the efficiency of the proposed method.

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