An Exact Penalty Approach for Mixed Integer Nonlinear Programming Problems

An Exact Penalty Approach for Mixed Integer Nonlinear Programming Problems

We propose an exact penalty approach for solving mixed integer nonlinear programming (MINLP) problems by converting a general MINLP problem to a finite sequence of nonlinear programming (NLP) problems with only continuous variables. We express conditions of exactness for MINLP problems and show how...

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Veröffentlicht in:American journal of operations research 2011-09, Vol.1 (3), p.185-189
Hauptverfasser: Shandiz, Roohollah Aliakbari, Mahdavi-Amiri, Nezam
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Sprache:eng
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Constraints
Converting
Mathematical analysis
Mixed integer
Nonlinear programming
Operations research
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container_title American journal of operations research
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creator Shandiz, Roohollah Aliakbari
Mahdavi-Amiri, Nezam
description We propose an exact penalty approach for solving mixed integer nonlinear programming (MINLP) problems by converting a general MINLP problem to a finite sequence of nonlinear programming (NLP) problems with only continuous variables. We express conditions of exactness for MINLP problems and show how the exact penalty approach can be extended to constrained problems.
doi_str_mv 10.4236/ajor.2011.13021
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subjects Constraints
Converting
Mathematical analysis
Mixed integer
Nonlinear programming
Operations research
title An Exact Penalty Approach for Mixed Integer Nonlinear Programming Problems
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