A Boolean Penalty Method for Zero-One Nonlinear Programming

David Mauricio, Nelson Maculan

Research output: Contribution to journalArticle

10 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 languageAmerican English
Pages (from-to)343-354
Number of pages12
JournalJournal of Global Optimization
StatePublished - 1 Jan 2000
Externally publishedYes

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