Displaying similar documents to “Strict convex regularizations, proximal points and augmented lagrangians”

Une heuristique d'optimisation globale basée sur la -transformation

Alexandre Dolgui, Valery Sysoev (2010)

RAIRO - Operations Research

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In this paper, we study a heuristic algorithm for global optimization, which is based on the -transformation. We illustrate its behavior first, on a set of continuous non-convex objective functions – we search the global optimum of each function. Then, we give an example from combinatorial optimization. It concerns the optimization of scheduling rules parameters of a manufacturing system. Computational results are presented, they look encouraging.

On convex sets that minimize the average distance

Antoine Lemenant, Edoardo Mainini (2012)

ESAIM: Control, Optimisation and Calculus of Variations

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In this paper we study the compact and convex sets K ⊆ Ω ⊆ ℝ2that minimize ∫ Ω ( , K ) d + λ 1 Vol ( K ) + λ 2 Per ( K ) ∫ Ω dist ( x ,K ) d x + λ 1 Vol ( K ) + λ 2 Per ( K ) for some constantsλ 1 and λ 2, that could possibly be zero. We compute in particular the second order derivative of the functional and use...

Multi-objective geometric programming problem with Karush−Kuhn−Tucker condition using ϵ-constraint method

A. K. Ojha, Rashmi Ranjan Ota (2014)

RAIRO - Operations Research - Recherche Opérationnelle

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Optimization is an important tool widely used in formulation of the mathematical model and design of various decision making problems related to the science and engineering. Generally, the real world problems are occurring in the form of multi-criteria and multi-choice with certain constraints. There is no such single optimal solution exist which could optimize all the objective functions simultaneously. In this paper, -constraint method along with Karush−Kuhn−Tucker (KKT) condition...

Two dimensional optimal transportation problem for a distance cost with a convex constraint

Ping Chen, Feida Jiang, Xiaoping Yang (2013)

ESAIM: Control, Optimisation and Calculus of Variations

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We first prove existence and uniqueness of optimal transportation maps for the Monge’s problem associated to a cost function with a strictly convex constraint in the Euclidean plane ℝ. The cost function coincides with the Euclidean distance if the displacement  −  belongs to a given strictly convex set, and it is infinite otherwise. Secondly, we give a sufficient condition for existence and uniqueness of optimal transportation maps for the original Monge’s problem in ℝ. Finally, we get...

Minmax regret combinatorial optimization problems: an Algorithmic Perspective

Alfredo Candia-Véjar, Eduardo Álvarez-Miranda, Nelson Maculan (2011)

RAIRO - Operations Research

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Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, , where uncertainty...

Minmax regret combinatorial optimization problems: an Algorithmic Perspective

Alfredo Candia-Véjar, Eduardo Álvarez-Miranda, Nelson Maculan (2011)

RAIRO - Operations Research

Similarity:

Uncertainty in optimization is not a new ingredient. Diverse models considering uncertainty have been developed over the last 40 years. In our paper we essentially discuss a particular uncertainty model associated with combinatorial optimization problems, developed in the 90's and broadly studied in the past years. This approach named (in particular our emphasis is on the robust deviation criteria) is different from the classical approach for handling uncertainty, , where uncertainty...