An exact penalty function method for nonlinear mixed discrete programming problems

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 additi...

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Main Authors: Changjun, Y., Teo, Kok Lay, Bai, Y.
Format: Journal Article
Published: Springer Verlag 2013
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/39347
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author Changjun, Y.
Teo, Kok Lay
Bai, Y.
author_facet Changjun, Y.
Teo, Kok Lay
Bai, Y.
author_sort Changjun, Y.
building Curtin Institutional Repository
collection Online Access
description 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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institution Curtin University Malaysia
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publishDate 2013
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spelling curtin-20.500.11937-393472017-09-13T15:33:38Z An exact penalty function method for nonlinear mixed discrete programming problems Changjun, Y. Teo, Kok Lay Bai, Y. exact penalty function nonlinear mixed integer programming 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. 2013 Journal Article http://hdl.handle.net/20.500.11937/39347 10.1007/s11590-011-0391-2 Springer Verlag restricted
spellingShingle exact penalty function
nonlinear mixed integer programming
Changjun, Y.
Teo, Kok Lay
Bai, Y.
An exact penalty function method for nonlinear mixed discrete programming problems
title An exact penalty function method for nonlinear mixed discrete programming problems
title_full An exact penalty function method for nonlinear mixed discrete programming problems
title_fullStr An exact penalty function method for nonlinear mixed discrete programming problems
title_full_unstemmed An exact penalty function method for nonlinear mixed discrete programming problems
title_short An exact penalty function method for nonlinear mixed discrete programming problems
title_sort exact penalty function method for nonlinear mixed discrete programming problems
topic exact penalty function
nonlinear mixed integer programming
url http://hdl.handle.net/20.500.11937/39347