Search results for "objective"

showing 10 items of 505 documents

Optimization and analysis of processes with moving materials subjected to fatigue fracture and instability

2013

We study systems of traveling continuum modeling the web as a thin elastic plate of brittle material, traveling between a system of supports at a constant velocity, and subjected to bending, in-plane tension and small initial cracks. We study crack growth under cyclic in-plane tension and transverse buckling of the web analytically. We seek optimal in-plane tension that maximizes a performance vector function consisting of the number of cycles before fracture, the critical velocity and process effectiveness. The present way of applying optimization in the studies of fracture and stability is new and affords an analytical tool for process analysis. peerReviewed

Materials scienceGeneral MathematicstuottavuusAerospace EngineeringväsymismurtumaOcean EngineeringBendingInstabilitymoving materialsPhysics::GeophysicsstabiiliusBrittlenessta216Continuum ModelingCivil and Structural Engineeringbusiness.industryTension (physics)Mechanical EngineeringStructural engineeringstabilityCondensed Matter PhysicsCritical ionization velocityfatigue fracturemonitavoiteoptimointiBucklingmulti-objective optimizationMechanics of MaterialsAutomotive EngineeringFracture (geology)liikkuva materiaalibusiness
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On Constraint Handling in Surrogate-Assisted Evolutionary Many-Objective Optimization

2016

Surrogate-assisted evolutionary multiobjective optimization algorithms are often used to solve computationally expensive problems. But their efficacy on handling constrained optimization problems having more than three objectives has not been widely studied. Particularly the issue of how feasible and infeasible solutions are handled in generating a data set for training a surrogate has not received much attention. In this paper, we use a recently proposed Kriging-assisted evolutionary algorithm for many-objective optimization and investigate the effect of infeasible solutions on the performance of the surrogates. We assume that constraint functions are computationally inexpensive and consid…

Mathematical optimization021103 operations researchComputer scienceFeasible region0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyConstraint satisfactionMulti-objective optimizationConstraint (information theory)Data set0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingEvolutionary programming
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Interactive Multiobjective Robust Optimization with NIMBUS

2018

In this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behavio…

Mathematical optimization021103 operations researchComputer sciencepareto-tehokkuuspäätöksenteko0211 other engineering and technologiesPareto principlemultiple criteria decision makingRobust optimization02 engineering and technologyrobustnessinteractive methodsDecision makerMinimaxTwo stagesrobust Pareto optimalitymonitavoiteoptimointiepävarmuusMultiobjective optimization problemRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing
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IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization

2019

We propose a new interactive evolutionary multiobjective optimization method, IRA-EMO. At each iteration, the decision maker (DM) expresses her/his preferences as an interesting interval for objective function values. The DM also specifies the number of representative Pareto optimal solutions in these intervals referred to as regions of interest one wants to study. Finally, a real-life engineering three-objective optimization problem is used to demonstrate how IRA-EMO works in practice for finding the most preferred solution. peerReviewed

Mathematical optimization021103 operations researchOptimization problemComputer sciencemieltymykset0211 other engineering and technologiesReservation02 engineering and technologyInterval (mathematics)interactive methodsMulti-objective optimizationmonitavoiteoptimointievolutionary multi-objective optimization0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingregion of interestreference point
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Evolutionary multi-objective optimization algorithms for fuzzy portfolio selection

2016

Graphical abstractDisplay Omitted HighlightsWe consider a constrained three-objective optimization portfolio selection problem.We solve the problem by means of evolutionary multi-objective optimization.New mutation, crossover and reparation operators are designed for this problem.They are tested in several algorithms for a data set from the Spanish stock market.Results for two performance metrics reveal the effectiveness of the new operators. In this paper, we consider a recently proposed model for portfolio selection, called Mean-Downside Risk-Skewness (MDRS) model. This modelling approach takes into account both the multidimensional nature of the portfolio selection problem and the requir…

Mathematical optimization021103 operations researchOptimization problemCrossover0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyFuzzy logicMulti-objective optimization0202 electrical engineering electronic engineering information engineeringExpected returnPortfolio020201 artificial intelligence & image processingAlgorithmSoftwarePossibility theoryMathematicsApplied Soft Computing
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District metered area design through multicriteria and multiobjective optimization

2022

[EN] The design of district metered areas (DMA) in potable water supply systems is of paramount importance for water utilities to properly manage their systems. Concomitant to their main objective, namely, to deliver quality water to consumers, the benefits include leakage reduction and prompt reaction in cases of natural or malicious contamination events. Given the structure of a water distribution network (WDN), graph theory is the basis for DMA design, and clustering algorithms can be applied to perform the partitioning. However, such sectorization entails a number of network modifications (installing cut-off valves and metering and control devices) involving costs and operation changes,…

Mathematical optimization06.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todosGeneral Mathematicsgraph theoryGeneral Engineeringk-means clusteringk-means algorithmTOPSISGraph theorymetaheuristicfuzzy AHPdistrict metered areasMulti-objective optimizationwater distribution systemsmultiobjective optimizationMATEMATICA APLICADATOPSISMetaheuristicDecision makingFuzzy ahpMathematics
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Portfolio optimization using a credibility mean-absolute semi-deviation model

2015

We present a cardinality constrained credibility mean-absolute semi-deviation model.We prove relationships for possibility and credibility moments for LR-fuzzy variables.The return on a given portfolio is modeled by means of LR-type fuzzy variables.We solve the portfolio selection problem using an evolutionary procedure with a DSS.We select best portfolio from Pareto-front with a ranking strategy based on Fuzzy VaR. We introduce a cardinality constrained multi-objective optimization problem for generating efficient portfolios within a fuzzy mean-absolute deviation framework. We assume that the return on a given portfolio is modeled by means of LR-type fuzzy variables, whose credibility dist…

Mathematical optimizationActuarial scienceOptimization problemComputer scienceGeneral EngineeringEfficient frontierRisk–return spectrumFuzzy logicMulti-objective optimizationCredibility theoryComputer Science ApplicationsArtificial IntelligenceCredibilityGenetic algorithmFuzzy numberPortfolioStock marketPost-modern portfolio theoryPortfolio optimizationMembership functionExpert Systems with Applications
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Interactive Inverse Modeling Based Multiobjective Evolutionary Algorithm

2018

An interactive version of the inverse modeling based multiobjective evolutionary algorithm is presented. Instead of generating a representation of the whole Pareto optimal front, the algorithm aims at producing solutions in the regions where the decision maker is interested in. This is facilitated through an interactive solution process where the decision maker iteratively evaluates a set of solutions shown to her/him and the preference information obtained is used to adapt the search process of the algorithm. peerReviewed

Mathematical optimizationComputer scienceEvolutionary algorithmProcess (computing)Inverseinverse modelingDecision makermonitavoiteoptimointiMulti-objective optimizationSet (abstract data type)algoritmitmallinnusRepresentation (mathematics)Preference (economics)
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A fuzzy-logic based evolutionary multiobjective approach for automated distribution networks management

2004

In this paper, a methodology to treat constrained scheduling problems based on the repeated application of a fuzzy-logic-based multiobjective algorithm is presented. The application domain is that of automated distribution systems management. In particular, the problem of voltage regulation and power loses minimization is here considered. The classical formulation of the problem of optimal control of shunt capacitor banks and under load tap changers, ULTC, located at high voltage/medium voltage (HV/MV) substations has been coupled with the optimal control of tie-switches and capacitor banks on the feeders of a large radially operated meshed distribution system with the aim of attaining mini…

Mathematical optimizationComputer scienceFuzzy setEvolutionary algorithmHigh voltageOptimal controlFuzzy logicDynamic multiobjective optimization Fuzzy Logic Power distribution Voltage controlEvolutionary computationlaw.inventionScheduling (computing)Settore ING-IND/33 - Sistemi Elettrici Per L'EnergiaCapacitorlawVoltage regulationVoltageProceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)
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A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

2021

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.

Mathematical optimizationComputer scienceGeneral Mathematics0211 other engineering and technologiesEvolutionary algorithm02 engineering and technologyMulti-objective optimizationSet (abstract data type)path relinkingDiscrete optimization0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Center (algebra and category theory)multiobjective optimizationEngineering (miscellaneous)021103 operations researchOscillationlcsh:MathematicsWorkload<i>k</i>-balanced problemGreedy Randomized Adaptive Search Procedure (GRASP)lcsh:QA1-939strategic oscillationPath (graph theory)020201 artificial intelligence & image processingdiscrete optimization<i>k</i>-center problemMathematics
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