Integrality gap minimization heuristics for binary mixed integer nonlinear programming

We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)—versions 1 and 2, our heuristics are based on the solution of integrality gap minimization problems with a space partitioning scheme defined over the integer var...

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Vydané v:Journal of global optimization Ročník 71; číslo 3; s. 593 - 612
Hlavní autori: Melo, Wendel, Fampa, Marcia, Raupp, Fernanda
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.07.2018
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Springer Nature B.V
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Abstract We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)—versions 1 and 2, our heuristics are based on the solution of integrality gap minimization problems with a space partitioning scheme defined over the integer variables of the problem addressed. Computational results on a set of benchmark instances show that the proposed approaches present satisfactory results.
AbstractList We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)-versions 1 and 2, our heuristics are based on the solution of integrality gap minimization problems with a space partitioning scheme defined over the integer variables of the problem addressed. Computational results on a set of benchmark instances show that the proposed approaches present satisfactory results.
Audience Academic
Author Raupp, Fernanda
Melo, Wendel
Fampa, Marcia
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  surname: Melo
  fullname: Melo, Wendel
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  organization: College of Computer Science, Federal University of Uberlandia
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  givenname: Marcia
  surname: Fampa
  fullname: Fampa, Marcia
  organization: Institute of Mathematics and COPPE, Federal University of Rio de Janeiro
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  givenname: Fernanda
  surname: Raupp
  fullname: Raupp, Fernanda
  organization: National Laboratory for Scientific Computing (LNCC) of the Ministry of Science, Technology and Innovation
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Keywords Integrality gap minimization
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Binary mixed integer nonlinear programming
Heuristics
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PublicationSubtitle An International Journal Dealing with Theoretical and Computational Aspects of Seeking Global Optima and Their Applications in Science, Management and Engineering
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Snippet We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)—versions 1 and 2,...
We present two feasibility heuristics for binary mixed integer nonlinear programming. Called integrality gap minimization algorithm (IGMA)-versions 1 and 2,...
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SubjectTerms Algorithms
Computer Science
Heuristic
Mathematics
Mathematics and Statistics
Mixed integer
Nonlinear programming
Operations Research/Decision Theory
Optimization
Real Functions
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Title Integrality gap minimization heuristics for binary mixed integer nonlinear programming
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