Penalty formulation for zero-one nonlinear programming

Bahman Kalantari, J. B. Rosen

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Raghavachari has shown the equivalence of zero-one integer programming and a concave quadratic penalty function for a sufficiently large value of the penalty. A lower bound for this penalty was found by Kalantari and Rosen. It was also shown that this penalty could not be reduced in specific cases. We show that the results generalize to the case where the objective function is any concave function. Equivalent penalty formulation for non-concave functions is also considered.

Original languageEnglish (US)
Pages (from-to)179-182
Number of pages4
JournalDiscrete Applied Mathematics
Volume16
Issue number2
DOIs
StatePublished - Jan 1 1987

Fingerprint

Nonlinear programming
Nonlinear Programming
Penalty
Formulation
Zero
Concave function
Integer programming
Penalty Function
Integer Programming
Quadratic Function
Objective function
Equivalence
Lower bound
Generalise

All Science Journal Classification (ASJC) codes

  • Discrete Mathematics and Combinatorics
  • Applied Mathematics

Keywords

  • Penalty formulations
  • concave minimization
  • global optimization

Cite this

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Penalty formulation for zero-one nonlinear programming. / Kalantari, Bahman; Rosen, J. B.

In: Discrete Applied Mathematics, Vol. 16, No. 2, 01.01.1987, p. 179-182.

Research output: Contribution to journalArticle

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