Derivative-free methods for mixed-integer nonsmooth constrained optimization

In this paper, mixed-integer nonsmooth constrained optimization problems are considered, where objective/constraint functions are available only as the output of a black-box zeroth-order oracle that does not provide derivative information. A new derivative-free linesearch-based algorithmic framework...

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Veröffentlicht in:Computational optimization and applications Jg. 82; H. 2; S. 293 - 327
Hauptverfasser: Giovannelli, Tommaso, Liuzzi, Giampaolo, Lucidi, Stefano, Rinaldi, Francesco
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.06.2022
Springer Nature B.V
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ISSN:0926-6003, 1573-2894
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Abstract In this paper, mixed-integer nonsmooth constrained optimization problems are considered, where objective/constraint functions are available only as the output of a black-box zeroth-order oracle that does not provide derivative information. A new derivative-free linesearch-based algorithmic framework is proposed to suitably handle those problems. First, a scheme for bound constrained problems that combines a dense sequence of directions to handle the nonsmoothness of the objective function with primitive directions to handle discrete variables is described. Then, an exact penalty approach is embedded in the scheme to suitably manage nonlinear (possibly nonsmooth) constraints. Global convergence properties of the proposed algorithms toward stationary points are analyzed and results of an extensive numerical experience on a set of mixed-integer test problems are reported.
AbstractList In this paper, mixed-integer nonsmooth constrained optimization problems are considered, where objective/constraint functions are available only as the output of a black-box zeroth-order oracle that does not provide derivative information. A new derivative-free linesearch-based algorithmic framework is proposed to suitably handle those problems. First, a scheme for bound constrained problems that combines a dense sequence of directions to handle the nonsmoothness of the objective function with primitive directions to handle discrete variables is described. Then, an exact penalty approach is embedded in the scheme to suitably manage nonlinear (possibly nonsmooth) constraints. Global convergence properties of the proposed algorithms toward stationary points are analyzed and results of an extensive numerical experience on a set of mixed-integer test problems are reported.
Author Giovannelli, Tommaso
Rinaldi, Francesco
Lucidi, Stefano
Liuzzi, Giampaolo
Author_xml – sequence: 1
  givenname: Tommaso
  surname: Giovannelli
  fullname: Giovannelli, Tommaso
  organization: Department of Industrial and Systems Engineering, Lehigh University
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  givenname: Giampaolo
  orcidid: 0000-0002-4063-8370
  surname: Liuzzi
  fullname: Liuzzi, Giampaolo
  email: liuzzi@diag.uniroma1.it
  organization: Dipartimento di Ingegneria Informatica, Automatica e Gestionale, Sapienza Università di Roma and Istituto di Analisi dei Sistemi e Informatica (IASI), CNR
– sequence: 3
  givenname: Stefano
  surname: Lucidi
  fullname: Lucidi, Stefano
  organization: Dipartimento di Ingegneria Informatica, Automatica e Gestionale, Sapienza Università di Roma
– sequence: 4
  givenname: Francesco
  surname: Rinaldi
  fullname: Rinaldi, Francesco
  organization: Dipartimento di Matematica “Tullio Levi-Civita”, Università di Padova
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Keywords Nonsmooth optimization
65K05
Mixed-integer nonlinear programming
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Derivative-free optimization
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Snippet In this paper, mixed-integer nonsmooth constrained optimization problems are considered, where objective/constraint functions are available only as the output...
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SubjectTerms Algorithms
Constraints
Convex and Discrete Geometry
Derivatives
Management Science
Mathematics
Mathematics and Statistics
Mixed integer
Operations Research
Operations Research/Decision Theory
Optimization
Statistics
Variables
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Title Derivative-free methods for mixed-integer nonsmooth constrained optimization
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