Search results for " robust optimization"

showing 4 items of 4 documents

Robust optimality of linear saturated control in uncertain linear network flows

2008

We propose a novel approach that, given a linear saturated feedback control policy, asks for the objective function that makes robust optimal such a policy. The approach is specialized to a linear network flow system with unknown but bounded demand and politopic bounds on controlled flows. All results are derived via the Hamilton-Jacobi-Isaacs and viscosity theory.

Inventory controlMathematical optimizationControl theoryViscosity (programming)Bounded functionLinear systemOptimal control Robust optimization Inventory control Viscosity solutionsTrajectoryRobust optimizationSettore MAT/09 - Ricerca OperativaRobust controlOptimal controlMathematics2008 47th IEEE Conference on Decision and Control
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The price of multiobjective robustness : Analyzing solution sets to uncertain multiobjective problems

2021

Defining and finding robust efficient solutions to uncertain multiobjective optimization problems has been an issue of growing interest recently. Different concepts have been published defining what a “robust efficient” solution is. Each of these concepts leads to a different set of solutions, but it is difficult to visualize and understand the differences between these sets. In this paper we develop an approach for comparing such sets of robust efficient solutions, namely we analyze their outcomes under the nominal scenario and in the worst case using the upper set-less order from set-valued optimization. Analyzing the set of nominal efficient solutions, the set of minmax robust efficient …

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputer sciencemultiobjective robust optimizationSolution setpäätöksentukijärjestelmätManagement Science and Operations ResearchMinimaxmonitavoiteoptimointiepävarmuusIndustrial and Manufacturing Engineeringdecision makingRobustness (computer science)Modeling and Simulationuncertaintyprice of robustness
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Decision making in multiobjective optimization problems under uncertainty: balancing between robustness and quality

2018

As an emerging research field, multiobjective robust optimization employs minmax robustness as the most commonly used concept. Light robustness is a concept in which a parameter, tolerable degradations, can be used to control the loss in the objective function values in the most typical scenario for gaining in robustness. In this paper, we develop a lightly robust interactive multiobjective optimization method, LiRoMo, to support a decision maker to find a most preferred lightly robust efficient solution with a good balance between robustness and the objective function values in the most typical scenario. In LiRoMo, we formulate a lightly robust subproblem utilizing an achievement scalarizi…

Mathematical optimizationdecision supportOptimization problemmultiobjective robust optimizationComputer sciencepäätöksenteko0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchMulti-objective optimizationoptimointiRobustness (computer science)0502 economics and business050210 logistics & transportation021103 operations research05 social scienceslight robust efficiencyRobust optimizationinteractive methodshandling uncertaintyDecision makerMinimaxmonitavoiteoptimointiepävarmuusVisualizationMultiobjective optimization problemtrade-off between robustness and qualityBusiness Management and Accounting (miscellaneous)OR Spectrum
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Constrained Robust MultiObjective Optimization for Reactive Design in Distribution Systems

2006

This paper presents a new formulation including robustness of solution of constrained multiobjective design or reactive power compensation. The algorithm used for optimization is the NSGA-II (Non dominated Sorting Genetic Algorithm II) with a special crowded comparison operator for constraints handling. The need for including the issue of robustness of solutions derives from the simple observation that loads are uncertain in distribution systems and their estimation is often affected by errors. In design problems it is desirable to consider the loads with a certain range of variation. In this paper the NSGA-II algorithm is applied to efficiently solve the issue and the solutions attained co…

Settore ING-IND/33 - Sistemi Elettrici Per L'EnergiaDistribution systemMathematical optimizationDistribution networksRobustness (computer science)Stochastic processControl theoryGenetic algorithmOptimal reactive power design Multiobjective optimization robust optimization distribution systemsRobust optimizationAC powerMulti-objective optimizationMathematics2006 International Conference on Probabilistic Methods Applied to Power Systems
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