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dc.contributor.authorChangjun, Y.
dc.contributor.authorTeo, Kok Lay
dc.contributor.authorBai, Y.
dc.identifier.citationChangjun, 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.

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.

dc.publisherSpringer Verlag
dc.subjectexact penalty function
dc.subjectnonlinear mixed integer programming
dc.titleAn exact penalty function method for nonlinear mixed discrete programming problems
dc.typeJournal Article
dcterms.source.titleOptimization Letters
curtin.accessStatusFulltext not available

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