Interactive multi-objective optimization for simulated moving bed processes
Jussi Hakanen, Yoshiaki Kawajiri, Kaisa Miettinen, Lorenz Biegler (2007)
Control and Cybernetics
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Jussi Hakanen, Yoshiaki Kawajiri, Kaisa Miettinen, Lorenz Biegler (2007)
Control and Cybernetics
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Marek Libura (2009)
Control and Cybernetics
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Luo, Xiao, Chung, Chi-Yung, Yang, Hongming, Tong, Xiaojiao (2011)
Mathematical Problems in Engineering
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Agnieszka Malinowska (2006)
Control and Cybernetics
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Petr Fiala (2011)
Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica
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Mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives. In multiobjective linear programming problems it is usually impossible to optimize all objectives in a given system. Trade-offs are properties of inadequately designed system a thus can be eliminated through designing better one. Multiobjective De Novo linear programming is problem for designing...
Michel Minoux (2014)
RAIRO - Operations Research - Recherche Opérationnelle
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The present paper addresses the class of two-stage robust optimization problems which can be formulated as mathematical programs with uncertainty on the right-hand side coefficients (RHS uncertainty). The wide variety of applications and the fact that many problems in the class have been shown to be NP-hard, motivates the search for efficiently solvable special cases. Accordingly, the first objective of the paper is to provide an overview of the most important applications and of various...
Frédéric de Gournay, Grégoire Allaire, François Jouve (2010)
ESAIM: Control, Optimisation and Calculus of Variations
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The goal of this paper is to study the so-called worst-case or robust optimal design problem for minimal compliance. In the context of linear elasticity we seek an optimal shape which minimizes the largest, or worst, compliance when the loads are subject to some unknown perturbations. We first prove that, for a fixed shape, there exists indeed a worst perturbation (possibly non unique) that we characterize as the maximizer of a nonlinear energy. We also propose a stable algorithm...