Proximal-gradient algorithms for fractional programming

In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a...

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Vydané v:Optimization Ročník 66; číslo 8; s. 1383 - 1396
Hlavní autori: Boţ, Radu Ioan, Csetnek, Ernö Robert
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Philadelphia Taylor & Francis 03.08.2017
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Abstract In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with respect to the nonsmooth numerator and a gradient step with respect to the smooth denominator. The algorithm in case of a concave denominator has the particularity that it generates sequences which approach both the (global) optimal solutions set and the optimal objective value of the underlying fractional programming problem. In case of a convex denominator the numerical scheme approaches the set of critical points of the objective function, provided the latter satisfies the Kurdyka-ᴌojasiewicz property.
AbstractList In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with respect to the nonsmooth numerator and a gradient step with respect to the smooth denominator. The algorithm in case of a concave denominator has the particularity that it generates sequences which approach both the (global) optimal solutions set and the optimal objective value of the underlying fractional programming problem. In case of a convex denominator the numerical scheme approaches the set of critical points of the objective function, provided the latter satisfies the Kurdyka-ᴌojasiewicz property.
In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with respect to the nonsmooth numerator and a gradient step with respect to the smooth denominator. The algorithm in case of a concave denominator has the particularity that it generates sequences which approach both the (global) optimal solutions set and the optimal objective value of the underlying fractional programming problem. In case of a convex denominator the numerical scheme approaches the set of critical points of the objective function, provided the latter satisfies the Kurdyka-ᴌojasiewicz property.In this paper, we propose two proximal-gradient algorithms for fractional programming problems in real Hilbert spaces, where the numerator is a proper, convex and lower semicontinuous function and the denominator is a smooth function, either concave or convex. In the iterative schemes, we perform a proximal step with respect to the nonsmooth numerator and a gradient step with respect to the smooth denominator. The algorithm in case of a concave denominator has the particularity that it generates sequences which approach both the (global) optimal solutions set and the optimal objective value of the underlying fractional programming problem. In case of a convex denominator the numerical scheme approaches the set of critical points of the objective function, provided the latter satisfies the Kurdyka-ᴌojasiewicz property.
Author Boţ, Radu Ioan
Csetnek, Ernö Robert
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Cites_doi 10.1137/060670080
10.1007/s10107-011-0484-9
10.1007/s10107-007-0133-5
10.1017/CBO9781139087322
10.1007/978-1-4419-8853-9
10.1287/moor.1100.0449
10.1007/s10107-013-0701-9
10.1090/S0002-9947-09-05048-X
10.1287/mnsc.13.7.492
10.5802/aif.1638
10.1142/9789812777096
10.1007/978-1-4471-4820-3
10.1007/978-3-642-02431-3
10.1007/BF00941314
10.1007/978-1-4419-9467-7
10.1007/s10957-013-0465-7
10.1007/BF02591871
10.1007/s13675-015-0045-8
10.1007/3-540-31247-1
10.1137/050644641
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References Ekeland I (CIT0008) 1976
CIT0010
CIT0021
CIT0020
CIT0001
CIT0012
CIT0023
CIT0022
Łojasiewicz S (CIT0016) 1963; 87
Ibaraki T (CIT0004) 1981
Schaible S (CIT0003) 1975; 22
CIT0014
CIT0002
CIT0013
CIT0024
CIT0005
Mordukhovich B (CIT0011) 2006
CIT0015
CIT0007
CIT0018
CIT0006
CIT0017
CIT0009
CIT0019
References_xml – ident: CIT0019
  doi: 10.1137/060670080
– ident: CIT0021
  doi: 10.1007/s10107-011-0484-9
– ident: CIT0022
  doi: 10.1007/s10107-007-0133-5
– ident: CIT0006
  doi: 10.1017/CBO9781139087322
– volume: 87
  year: 1963
  ident: CIT0016
  publication-title: Les Équations aux Dérivées Partielles, Éditions du Centre National de la Recherche Scientifique Paris
– ident: CIT0010
  doi: 10.1007/978-1-4419-8853-9
– ident: CIT0014
  doi: 10.1287/moor.1100.0449
– ident: CIT0015
  doi: 10.1007/s10107-013-0701-9
– ident: CIT0020
  doi: 10.1090/S0002-9947-09-05048-X
– ident: CIT0001
  doi: 10.1287/mnsc.13.7.492
– ident: CIT0017
  doi: 10.5802/aif.1638
– ident: CIT0009
  doi: 10.1142/9789812777096
– ident: CIT0013
  doi: 10.1007/978-1-4471-4820-3
– ident: CIT0012
  doi: 10.1007/978-3-642-02431-3
– ident: CIT0002
  doi: 10.1007/BF00941314
– ident: CIT0007
  doi: 10.1007/978-1-4419-9467-7
– ident: CIT0024
  doi: 10.1007/s10957-013-0465-7
– volume: 22
  start-page: 868
  issue: 8
  year: 1975
  ident: CIT0003
  publication-title: On Dinkelbach’s algorithm, Manage Sci
– ident: CIT0005
  doi: 10.1007/BF02591871
– volume-title: Convex analysis and variational problems
  year: 1976
  ident: CIT0008
– ident: CIT0023
  doi: 10.1007/s13675-015-0045-8
– start-page: 441
  volume-title: Generalized concavity in optimization and eeconomics
  year: 1981
  ident: CIT0004
– volume-title: Variational analysis and generalized differentiation, I: basic theory, II: applications
  year: 2006
  ident: CIT0011
  doi: 10.1007/3-540-31247-1
– ident: CIT0018
  doi: 10.1137/050644641
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SubjectTerms Algorithms
convergence rate
convex subdifferential
forward-backward algorithm
Fractional programming
Iterative methods
Kurdyka-ᴌojasiewicz property
limiting subdifferential
Mathematical programming
Programming
Title Proximal-gradient algorithms for fractional programming
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