Optimality Conditions and a Method of Centers for Minimax Fractional Programs with Difference of Convex Functions

We are concerned in this paper with minimax fractional programs whose objective functions are the maximum of finite ratios of difference of convex functions, with constraints also described by difference of convex functions. Like Dinkelbach-type algorithms, the method of centers for generalized frac...

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Veröffentlicht in:Journal of optimization theory and applications Jg. 187; H. 1; S. 105 - 132
Hauptverfasser: Boufi, Karima, El Haffari, Mostafa, Roubi, Ahmed
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.10.2020
Springer Nature B.V
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ISSN:0022-3239, 1573-2878
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Abstract We are concerned in this paper with minimax fractional programs whose objective functions are the maximum of finite ratios of difference of convex functions, with constraints also described by difference of convex functions. Like Dinkelbach-type algorithms, the method of centers for generalized fractional programs fails to work for such problems, since the parametric subproblems may be nonconvex, whereas the latters need a global optimal solution for these subproblems. We first give necessary optimality conditions for these problems, by means of convex analysis tools, and then extend the last method to solve such programs. The method is based on solving a sequence of parametric convex problems. We show that every cluster point of the sequence of optimal solutions of these subproblems satisfies necessary optimality conditions of Karush–Kuhn–Tucker criticality type.
AbstractList We are concerned in this paper with minimax fractional programs whose objective functions are the maximum of finite ratios of difference of convex functions, with constraints also described by difference of convex functions. Like Dinkelbach-type algorithms, the method of centers for generalized fractional programs fails to work for such problems, since the parametric subproblems may be nonconvex, whereas the latters need a global optimal solution for these subproblems. We first give necessary optimality conditions for these problems, by means of convex analysis tools, and then extend the last method to solve such programs. The method is based on solving a sequence of parametric convex problems. We show that every cluster point of the sequence of optimal solutions of these subproblems satisfies necessary optimality conditions of Karush–Kuhn–Tucker criticality type.
Author El Haffari, Mostafa
Roubi, Ahmed
Boufi, Karima
Author_xml – sequence: 1
  givenname: Karima
  surname: Boufi
  fullname: Boufi, Karima
  organization: Laboratoire MISI, Faculté des Sciences et Techniques, Univ. Hassan 1
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  givenname: Mostafa
  surname: El Haffari
  fullname: El Haffari, Mostafa
  organization: Laboratoire MISI & Ecole Normale Supérieure, Univ. Abdelmalek Essaâdi
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  givenname: Ahmed
  surname: Roubi
  fullname: Roubi, Ahmed
  email: roubia@hotmail.com
  organization: Laboratoire MISI, Faculté des Sciences et Techniques, Univ. Hassan 1
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Keywords Optimality conditions
90C32
90C46
90C25
90C47
Difference of convex functions
Method of centers
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Fractional programming
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Snippet We are concerned in this paper with minimax fractional programs whose objective functions are the maximum of finite ratios of difference of convex functions,...
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SubjectTerms Algorithms
Applications of Mathematics
Calculus of Variations and Optimal Control; Optimization
Convex analysis
Engineering
Mathematical programming
Mathematics
Mathematics and Statistics
Minimax technique
Operations Research/Decision Theory
Optimization
Theory of Computation
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Title Optimality Conditions and a Method of Centers for Minimax Fractional Programs with Difference of Convex Functions
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