Search results for "Linear programming"

showing 10 items of 137 documents

Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms

2016

We study how different types of preference information coming from a human decision maker can be utilized in an interactive multiobjective evolutionary optimization algorithm (MOEA). The idea is to convert different types of preference information into a unified format which can then be utilized in an interactive MOEA to guide the search towards the most preferred solution(s). The format chosen here is a set of reference vectors which is used within the interactive version of the reference vector guided evolutionary algorithm (RVEA). The proposed interactive RVEA is then applied to the multiple-disk clutch brake design problem with five objectives to demonstrate the potential of the idea in…

Optimization problemLinear programmingComputer science0211 other engineering and technologiesEvolutionary algorithmInteractive evolutionary computationpreference information02 engineering and technologyMachine learningcomputer.software_genredecision makingEvolutionary computationSet (abstract data type)vectors0202 electrical engineering electronic engineering information engineeringta113021103 operations researchbusiness.industryta111Approximation algorithmPreferencemultiobjective evolutionary optimization algorithm020201 artificial intelligence & image processingArtificial intelligencebusinessoptimizationcomputer2016 IEEE Symposium Series on Computational Intelligence (SSCI)
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Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles

2019

Multi-label classification deals with the task of predicting multiple class labels for a given sample. Several performance metrics are designed in the literature to measure the quality of any multi-label classification technique. In general existing multi-label classification approaches focus on optimizing only a single performance measure. The current work builds on the hypothesis that a weighted ensemble of multiple multi-label classifiers will lead to obtain improved results. The appropriate weight combinations for combining the outputs of multiple classifiers can be selected after simultaneously optimizing different multi-label classification metrics like micro F1, hamming loss, 0/1 los…

Optimization problemLinear programmingbusiness.industryComputer science02 engineering and technologyMachine learningcomputer.software_genreMulti-objective optimizationComputingMethodologies_PATTERNRECOGNITION020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)computer2019 IEEE Congress on Evolutionary Computation (CEC)
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Energy Management Systems and tertiary regulation in hierarchical control architectures for islanded microgrids

2015

In this paper, the structure of the highest level of a hierarchical control architecture for micro-grids is proposed. Such structure includes two sub-levels: the Energy Management System, EMS, and the tertiary regulation. The first devoted to energy resources allocation in each time slot based on marginal production costs, the latter aiming at finding the match between production and consumption satisfying the constraints set by the EMS level about the energy production in each time slot. Neglecting the efficiency of the different energy generation systems as well as that of the infrastructure for electrical energy distribution, the problem dealt with by the EMS sub-level is linear and can …

OptimizationEngineeringMathematical optimizationMicro-gridsLinear programmingEnergy managementbusiness.industry:Energies [Àrees temàtiques de la UPC]Electric potential energyControl engineeringElectric powerEnergy management systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaElectricity generationEnergy management systemsLinear programmingEnergia elèctricaElectric powerMinificationbusinessInteger programmingEnergy management systems linear programming microgrids optimization
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Multi Sources Water Supply System Optimal Control: A Case Study

2014

The optimal operation of a multi quality network was analysed applying Linear Programming methods. The peculiar service condition of the industrial city of Gela (Italy) was investigated. The network is supplied both from waters derived from a desalination plant and other natural sources. The method aimed to minimise energy cost and find the optimal operation control, while satisfying demand and quality constraints, specifically with regard to water temperature. The method proved to be effective in the selection of the optimal management strategy after the definition of a specific water quality target. (C) 2014 Published by Elsevier Ltd.

OptimizationEngineeringMathematical optimizationmulti source supplyLinear programmingbusiness.industrymedia_common.quotation_subjectEnvironmental engineeringWater supplymulti source supply.General MedicineOptimal controlDesalinationwater qualityOptimal managementdesalinationQuality (business)Water qualitybusinessSelection (genetic algorithm)Engineering(all)media_common
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On the Reliability of Optimization Results for Trigeneration Systems in Buildings, in the Presence of Price Uncertainties and Erroneous Load Estimati…

2016

Cogeneration and trigeneration plants are widely recognized as promising technologies for increasing energy efficiency in buildings. However, their overall potential is scarcely exploited, due to the difficulties in achieving economic viability and the risk of investment related to uncertainties in future energy loads and prices. Several stochastic optimization models have been proposed in the literature to account for uncertainties, but these instruments share in a common reliance on user-defined probability functions for each stochastic parameter. Being such functions hard to predict, in this paper an analysis of the influence of erroneous estimation of the uncertain energy loads and pric…

OptimizationMathematical optimizationEngineeringenergy loadControl and OptimizationLinear programming020209 energyEnergy Engineering and Power TechnologyPrice02 engineering and technologycogeneration; trigeneration; buildings; optimization; linear programming; stochastic; uncertainty; sensitivity; energy loads; priceslcsh:TechnologyCogenerationbuildingSettore ING-IND/10 - Fisica Tecnica Industriale0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringEngineering (miscellaneous)Integer programminglcsh:TTrigenerationRenewable Energy Sustainability and the Environmentbusiness.industryUncertaintylinear programmingcogenerationsensitivitybuildingsStochasticPower (physics)energy loadsProfitability indexStochastic optimizationElectricitybusinesspricesEnergy (miscellaneous)Efficient energy useEnergies; Volume 9; Issue 12; Pages: 1049
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Interactive Nonlinear Multiobjective Optimization Methods

2016

An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory Pareto optimal solution can be found for her or his. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated. As the role of the decision maker is very important in interactive methods, methods presented are classified according to the type of preference information that the decision maker is assumed to provide. peerReviewed

Pareto optimalityMathematical optimization021103 operations researchComputer sciencemultiple criteria decision making0211 other engineering and technologies02 engineering and technologyinteractive methodsDecision makernonlinear optimizationMulti-objective optimizationPreferenceNonlinear programmingPareto optimalNonlinear systemMultiobjective optimization problemmultiple objectives0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing
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Optimal Impulse Control Problems and Linear Programming

2009

Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, we present a solution algorithm that converges to the exact solution in polynomial time. Our approach consists in approximating the optimal impulse control problem via a binary linear programming proble…

PolynomialMathematical optimizationUnimodular matrixComputational complexity theoryLinear programmingbusiness.industryImpulse control hybrid systems optimal controlLocal search (optimization)Relaxation (approximation)Optimal controlbusinessTime complexityMathematics
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Multi-stage Linear Programming Optimization for Pump Scheduling

2014

This study presents a methodology based on Linear Programming for determining the optimal pump schedule on a 24-hour basis, considering as decision variables the continuous pump flow rates which are subsequently transformed into a discrete schedule. The methodology was applied on a case study derived from the benchmark Anytown network. To evaluate the LP reliability, a comparison was made with solutions generated by a Hybrid Discrete Dynamically Dimensioned Search (HD-DDS) algorithm. The cost associated with the result derived from the LP initial solution was shown to be lower than that obtained with repeated HD-DDS runs with differing random seeds. (C) 2013 The Authors. Published by Elsevi…

Pump schedulingOptimizationEngineeringMathematical optimizationLinear programmingbusiness.industryGeneral MedicineHD-DDSScheduling (computing)Pump flowMulti stageDecision variablesLinear ProgrammingbusinessEngineering(all)Procedia Engineering
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A combined approach of SGBEM and conic quadratic optimization for limit analysis

2011

The static approach to evaluate the limit multiplier directly was rephrased using the Symmetric Galerkin Boundary Element Method (SGBEM) for multidomain type problems [1,2]. The present formulation couples SGBEM multidomain procedure with nonlinear optimization techniques, making use of the self-equilibrium stress equation [3-5]. This equation connects the stresses at the Gauss points of each substructure (bem-e) to plastic strains through a self-stress matrix computed in all the bem-elements of the discretized system. The analysis was performed by means of a conic quadratic optimization problem, in terms of discrete variables, and implemented using Karnak.sGbem code [6] coupled with MathLa…

SGBEM multidomain lower bound limit analysis nonlinear programming
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Flexibility Services to Minimize the Electricity Production from Fossil Fuels. A Case Study in a Mediterranean Small Island

2019

The design of multi-carrier energy systems (MESs) has become increasingly important in the last decades, due to the need to move towards more efficient, flexible, and reliable power systems. In a MES, electricity, heating, cooling, water, and other resources interact at various levels, in order to get optimized operation. The aim of this study is to identify the optimal combination of components, their optimal sizes, and operating schedule allowing minimizing the annual cost for meeting the energy demand of Pantelleria, a Mediterranean island. Starting from the existing energy system (comprising diesel generators, desalination plant, freshwater storage, heat pumps, and domestic hot water st…

ScheduleControl and Optimization020209 energyEnergy Engineering and Power TechnologyMulti-carrier energy system02 engineering and technology010501 environmental sciencesmixed integer linear programming01 natural sciencesDesalinationlcsh:Technologyenergy hubElectric power systemmulti-carrier energy systems; energy hubs; mixed integer linear programming; optimization; islands energy system0202 electrical engineering electronic engineering information engineeringenergy hubsElectrical and Electronic EngineeringProcess engineeringEngineering (miscellaneous)Integer programming0105 earth and related environmental sciencesSettore ING-IND/11 - Fisica Tecnica AmbientaleRenewable Energy Sustainability and the Environmentbusiness.industrylcsh:TPhotovoltaic systemFossil fuelmulti-carrier energy systemsislands energy systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaElectricity generationEnvironmental scienceElectricitybusinessoptimizationEnergy (miscellaneous)Energies; Volume 12; Issue 18; Pages: 3492
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