Displaying similar documents to “Two-stage robust optimization, state-space representable uncertainty and applications”

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...

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...

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.