Variationally-derived limited-memory methods for unconstrained optimization
Vlček, Jan, Lukšan, Ladislav
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Displaying similar documents to “The Mean-Variance-CVaR model for Portfolio Optimization Modeling using a Multi-Objective Approach Based on a Hybrid Method”
Variationally-derived limited-memory methods for unconstrained optimization
On an optimization problem described by some integral equations
Pelczewski, Jerzy (2015-11-28T13:30:03Z)
Acta Universitatis Lodziensis. Folia Mathematica
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An Optimization Procedure for Water Reservoir Planning
Serafim Opricović, Lorenzo Eccher, Miodrag Isailovski (1991)
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S. Grzegórski, H. Popławska (1974)
Applicationes Mathematicae
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A method of scalarization of Bacopoulos und Singer in vectorial optimization
Rzepecka, Genowefa (2015-11-10T13:18:06Z)
Acta Universitatis Lodziensis. Folia Mathematica
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Nonessential objective functions in linear multiobjective optimization problems
Agnieszka Malinowska (2006)
Control and Cybernetics
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On approximating NP-hard optimization problems.
Håstad, Johan (1998)
Documenta Mathematica
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Combinatorial optimization in production and logistics systems
Christelle Guéret, Eric Pinson, David Rivreau (2013)
RAIRO - Operations Research - Recherche Opérationnelle
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Multi-objective Optimization Problem with Bounded Parameters
Ajay Kumar Bhurjee, Geetanjali Panda (2014)
RAIRO - Operations Research - Recherche Opérationnelle
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In this paper, we propose a nonlinear multi-objective optimization problem whose parameters in the objective functions and constraints vary in between some lower and upper bounds. Existence of the efficient solution of this model is studied and gradient based as well as gradient free optimality conditions are derived. The theoretical developments are illustrated through numerical examples.