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

Boufi, Karima; Haffari, Mostafa El; Roubi, Ahmed

doi:10.1007/s10957-020-01738-2

J Optim Theory Appl

2020

DOI: 10.1007/s10957-020-01738-2

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

Karima Boufi

Mostafa El Haffari

Ahmed Roubi

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Cited by 4 publications

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“…In the literature, there have been two types of algorithms for solving a GFP, primal Dinkelbach-type algorithms [10,17,18,19,21,40,39,51,28,13]; and dual algorithms [2,3,7,8,9,11,12,14,15,16,20,22,23,31]. See also [45,46,50,49,47,48] for more references on fractional programming.…”

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confidence: 99%

Augmented Lagrangian dual for nonconvex minimax fractional programs and proximal bundle algorithms for its resolution

Boualam¹,

Roubi²

2023

JIMO

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<p style='text-indent:20px;'>Based on augmented Lagrangian, we propose in this paper a new dual for inequality constrained nonconvex generalized fractional programs (GFP). We give duality results under quite weak assumptions. We associate with this dual program, parametric dual subproblems and establish duality results with the usual parametric primal ones. By taking advantage of the concavity of the parametric dual functions, we propose proximal bundle-like methods that approximately solve the parametric dual subproblems, to finally solve this dual program. For some problems, these method converge linearly.</p>

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confidence: 99%

Augmented Lagrangian dual for nonconvex minimax fractional programs and proximal bundle algorithms for its resolution

Boualam¹,

Roubi²

2023

JIMO

Self Cite

View full text Add to dashboard Cite

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Optimality conditions and DC-Dinkelbach-type algorithm for generalized fractional programs with ratios of difference of convex functions

Ghazi

Roubi

2021

Optim Lett

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Solving min–max linear fractional programs based on image space branch-and-bound scheme

Jiao

2022

Chaos, Solitons & Fractals

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

Cited by 4 publications

References 38 publications

Augmented Lagrangian dual for nonconvex minimax fractional programs and proximal bundle algorithms for its resolution

Augmented Lagrangian dual for nonconvex minimax fractional programs and proximal bundle algorithms for its resolution

Optimality conditions and DC-Dinkelbach-type algorithm for generalized fractional programs with ratios of difference of convex functions

Solving min–max linear fractional programs based on image space branch-and-bound scheme

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