Convergence of a proximal algorithm for solving the dual of a generalized fractional program
RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 985-1004.

We propose to use the proximal point algorithm to regularize a “dual” problem of generalized fractional programs (GFP). The proposed technique leads to a new dual algorithm that generates a sequence which converges from below to the minimal value of the considered problem. At each step, the proposed algorithm solves approximately an auxiliary problem with a unique dual solution whose every cluster point gives a solution to the dual problem. In the exact minimization case, the sequence of dual solutions converges to an optimal dual solution. For a class of functions, including the linear case, the convergence of the dual values is at least linear.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2017004
Classification : 90C30, 90C32, 49K35, 49M29, 49M37
Mots-clés : Multi-ratio fractional programs, Dinkelbach-type algorithms, Lagrange duality, proximal point algorithm
El Haffari, Mostafa 1 ; Roubi, Ahmed 1

1 Faculté des Sciences et Techniques, Settat, Morocco.
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El Haffari, Mostafa; Roubi, Ahmed. Convergence of a proximal algorithm for solving the dual of a generalized fractional program. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 4, pp. 985-1004. doi : 10.1051/ro/2017004. http://www.numdam.org/articles/10.1051/ro/2017004/

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