A Boolean Penalty Method for Zero-One Nonlinear Programming

David Mauricio, Nelson Maculan

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


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 languageEnglish
Pages (from-to)343-354
Number of pages12
JournalJournal of Global Optimization
Issue number4
StatePublished - 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.


  • 0-1 nonlinear programming
  • Combinatorial optimization
  • Discrete penalty


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