Search results for "constrained optimization"

showing 10 items of 26 documents

Constraint handling in efficient global optimization

2017

Real-world optimization problems are often subject to several constraints which are expensive to evaluate in terms of cost or time. Although a lot of effort is devoted to make use of surrogate models for expensive optimization tasks, not many strong surrogate-assisted algorithms can address the challenging constrained problems. Efficient Global Optimization (EGO) is a Kriging-based surrogate-assisted algorithm. It was originally proposed to address unconstrained problems and later was modified to solve constrained problems. However, these type of algorithms still suffer from several issues, mainly: (1) early stagnation, (2) problems with multiple active constraints and (3) frequent crashes.…

Mathematical optimizationConstraint optimizationOptimization problemL-reduction0211 other engineering and technologiesGaussian processes02 engineering and technologyexpensive optimizationMulti-objective optimizationEngineering optimizationSurrogate modelsKriging0202 electrical engineering electronic engineering information engineeringMulti-swarm optimizationGlobal optimization/dk/atira/pure/subjectarea/asjc/1700/1712constraint optimizationMathematicsta113EGO/dk/atira/pure/subjectarea/asjc/1700/1706Expensive optimization021103 operations researchConstrained optimizationComputer Science Applicationssurrogate modelsKrigingComputational Theory and Mathematics020201 artificial intelligence & image processing/dk/atira/pure/subjectarea/asjc/1700/1703SoftwareProceedings of the Genetic and Evolutionary Computation Conference
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Adaptive memory programming for constrained global optimization

2010

The problem of finding a global optimum of a constrained multimodal function has been the subject of intensive study in recent years. Several effective global optimization algorithms for constrained problems have been developed; among them, the multi-start procedures discussed in Ugray et al. [1] are the most effective. We present some new multi-start methods based on the framework of adaptive memory programming (AMP), which involve memory structures that are superimposed on a local optimizer. Computational comparisons involving widely used gradient-based local solvers, such as Conopt and OQNLP, are performed on a testbed of 41 problems that have been used to calibrate the performance of su…

Mathematical optimizationGlobal optimumGeneral Computer ScienceMultimodal functionAdaptive methodModeling and SimulationTestbedConstrained optimizationManagement Science and Operations ResearchGlobal optimizationTabu searchAdaptive memory programmingMathematicsComputers & Operations Research
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A new branch-and-price algorithm for the traveling tournament problem

2010

Abstract The traveling tournament problem ( ttp ) consists of finding a distance-minimal double round-robin tournament where the number of consecutive breaks is bounded. For solving the problem exactly, we propose a new branch-and-price approach. The starting point is a new compact formulation for the ttp . The corresponding extensive formulation resulting from a Dantzig-Wolfe decomposition is identical to one given by Easton, K., Nemhauser, G., Trick, M., 2003. Solving the traveling tournament problem: a combined interger programming and constraint programming approach. In: Burke, E., De Causmaecker, P. (Eds.), Practice and Theory of Automated Timetabling IV, Volume 2740 of Lecture Notes i…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceBranch and priceConstrained optimizationManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringReduction (complexity)Exact algorithmModeling and SimulationShortest path problemConstraint programmingColumn generationVariable eliminationMathematicsEuropean Journal of Operational Research
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A fuzzy method to repair infeasibility in linearly constrained problems

2001

Abstract In this paper we introduce a fuzzy method to deal with infeasibility in linearly constrained programs. Given an infeasible instance, we determine how much we should perturb the right-hand side coefficients in order to attain feasibility and propose a ‘feasible reformulation’ of the problem. Although we prove that our algorithm always finds such a reformulation the convenience of using it can be decided by the analyst. By this, we mean that the method also provides a simple way to compute lower bounds on the changes on every right-hand side coefficient, and if the decision maker considers that some of the magnitudes are unacceptable, he or she simply stops at this step. We think tha…

Mathematical optimizationLinear programmingArtificial IntelligenceLogicOrder (exchange)Simple (abstract algebra)Fuzzy setConstrained optimizationFuzzy methodAlgorithmUpper and lower boundsFuzzy logicMathematicsFuzzy Sets and Systems
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Approximations and Metric Regularity in Mathematical Programming in Banach Space

1993

This paper establishes verifiable conditions ensuring the important notion of metric regularity for general nondifferentiable programming problems in Banach spaces. These conditions are used to obtain Lagrange-Kuhn-Tucker multipliers for minimization problems with infinitely many inequality and equality constraints.

Minimisation (psychology)Mathematical optimizationGeneral MathematicsMathematics::Optimization and ControlConstrained optimizationBanach spaceSubderivativeManagement Science and Operations ResearchComputer Science Applicationssymbols.namesakeLagrange multiplierMetric (mathematics)symbolsVerifiable secret sharingMinificationMathematicsMathematics of Operations Research
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On State Constrained Optimal Shape Design Problems

1987

This paper is concerned with the following optimal design problem with constraints both on the state and on the control: $$MinimizeJ(y,u)$$ (P) subject to $$A\left( u \right)y + \partial \varphi \left( y \right) \mathrel\backepsilon Bu + f,$$ (1.1) $$y \in K,$$ (1.2) $$u \in {U_{ad}}.$$ (1.3)

Optimal designDiscrete mathematicsShape designVariational inequalityConstrained optimizationState (functional analysis)Mathematics
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Crowded comparison operators for constraints handling in NSGA-II for optimal design of the compensation system in electrical distribution networks

2006

This paper proposes an improvement of an efficient multiobjective optimization algorithm, Non-dominated Sorting Genetic Algorithm II, NSGA-II, that has been here applied to solve the problem of optimal capacitors placement in distribution systems. The studied improvement involves the Crowded Comparison Operator and modifies it in order to handle several constraints. The problem of optimal location and sizing of capacitor banks for losses reduction and voltage profile flattening in medium voltage (MV) automated distribution systems is a difficult combinatorial constrained optimization problem which is deeply studied in literature. In this paper, the efficiency of the proposed Crowded Compari…

Optimal designMathematical optimizationMultiobjective constrained optimizationSortingCompensation system designRelational operatorSizinglaw.inventionSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaReduction (complexity)CapacitorOperator (computer programming)Genetic algorithmConstraints handlingArtificial IntelligenceControl theorylawGenetic algorithmInformation SystemsMathematicsAdvanced Engineering Informatics
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Helmholtz equation in unbounded domains: some convergence results for a constrained optimization problem

2016

We consider a constrained optimization problem arising from the study of the Helmholtz equation in unbounded domains. The optimization problem provides an approximation of the solution in a bounded computational domain. In this paper we prove some estimates on the rate of convergence to the exact solution.

Optimization problemHelmholtz equationDomain (software engineering)Constrained optimization problemExact solutions in general relativityMathematics - Analysis of PDEsRate of convergenceBounded functionConvergence (routing)FOS: MathematicsHelmholtz equation Transparent boundary conditions Minimization of integral functionals.Applied mathematicsMathematicsAnalysis of PDEs (math.AP)
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Bluetooth Base Station Minimal Deployment for High Definition Positioning

2005

This paper discusses our approach to the problem of arranging a Bluetooth based positioning system capable of providing people coordinates in a given area with an accuracy as high as possible. Our strategy focuses on optimizing the disposition of a minimal number of available Bluetooth base stations in a subset of locations which are the only ones permitted by site characteristics and constraints. We used a genetic algorithm to this purpose and a layout chromosome whose best evolution suggested us how to deploy a minimal set of Bluetooth base stations. As a case study, we discuss our experiments and results which deal with a late middle age castle in Sicily where we carried out many trials.

Positioning systembusiness.industryComputer scienceConstrained optimizationlaw.inventionBluetoothBase stationChromosome (genetic algorithm)Software deploymentlawGenetic algorithmWirelessbusinessSimulationComputer network
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A Constrained Optimal Model Predictive Control for Mono Inverter Dual Parallel PMSM Drives

2018

The actual trends in the design of AC drives are directed to the reduction of the total weight, volume and cost. Usually, this implies the necessity to adopt new motor topologies and converter architectures. An important role is played by the mono-inverter dual parallel motor (MIDP), which gives the possibility to reduce the total weight and costs of power converters. This paper proposes a novel model predictive control algorithm in order to improve the transient performances of a MIDP used for an overhead carrier. The effectiveness of the proposal control is verified through some numerical simulations.

Renewable Energy Sustainability and the EnvironmentComputer scienceAC drive020209 energy020208 electrical & electronic engineeringConstrained optimizationEnergy Engineering and Power Technology02 engineering and technologyPermanent Magnet Synchronous MachineConvertersPower (physics)Reduction (complexity)Model predictive controlControl theory0202 electrical engineering electronic engineering information engineeringOverhead (computing)InverterTransient (oscillation)Electrical and Electronic EngineeringConstrained optimizationDual motorModel Predictive Control2018 7th International Conference on Renewable Energy Research and Applications (ICRERA)
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