A Boolean Penalty Method for Zero-One Nonlinear Programming

David Mauricio; Nelson Maculan

doi:10.1023/A:1008329405026

A Boolean Penalty Method for Zero-One Nonlinear Programming

David Mauricio, Nelson Maculan

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

We introduce a discrete penalty called Boolean Penalty to 0-1 constrained nonlinear programming (PNLC-01). The main importance of this Penalty function are its properties which allow us to develop algorithms for the PNLC-01 problem. Optimality conditions, and numerical results are presented.

Original language	English
Pages (from-to)	343-354
Number of pages	12
Journal	Journal of Global Optimization
Volume	16
Issue number	4
DOIs	https://doi.org/10.1023/A:1008329405026
State	Published - Apr 2000

Bibliographical note

Funding Information:
The authors wish to thank José Koiller for his helpful advice and suggestions. This work was partially supported by CNPq and FAPERJ.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Keywords

0-1 nonlinear programming
Combinatorial optimization
Discrete penalty

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A Boolean Penalty Method for Zero-One Nonlinear Programming

Abstract

Bibliographical note

Keywords

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