Search results for "linear programming"

showing 10 items of 137 documents

Sporta sacensību plānošana lietojot lineāro programmēšanu

2018

Darbā tiek analizēts diskrētās programmēšanas modelis sporta apļa turnīra grafika izveidei, minimizējot novirzi starp komandu priekšrocību sarakstu un rezultējošo grafiku. Tiek apskatīti speciālie matemātiskie rīki, lai panāktu stabilu risinājumu sacensību plānošanas problēmai. Īpaša uzmanība tiek pievērsta stabilitātes nosacījumam šī modeļa kontekstā. Tiek definēti komandu priekšrocību veidi un meklēti stabili un nestabili grafiki turnīriem pie dažādām priekšrocībām.

sporta sacensību plānošanapriekšrocību veidiMatemātikalinear programminglineārā programmēšanastabilitātes nosacījums
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On the equivalence of two optimization methods for fuzzy linear programming problems

2000

Abstract The paper analyses the linear programming problem with fuzzy coefficients in the objective function. The set of nondominated (ND) solutions with respect to an assumed fuzzy preference relation, according to Orlovsky's concept, is supposed to be the solution of the problem. Special attention is paid to unfuzzy nondominated (UND) solutions (the solutions which are nondominated to the degree one). The main results of the paper are sufficient conditions on a fuzzy preference relation allowing to reduce the problem of determining UND solutions to that of determining the optimal solutions of a classical linear programming problem. These solutions can thus be determined by means of classi…

Mathematical optimizationInformation Systems and ManagementFuzzy classificationGeneral Computer ScienceLinear programmingManagement Science and Operations ResearchFuzzy logicIndustrial and Manufacturing EngineeringLinear-fractional programmingFuzzy transportationModeling and SimulationFuzzy mathematicsFuzzy set operationsFuzzy numberMathematicsEuropean Journal of Operational Research
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Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system

2017

We tackle three different challenges in solving a real-world industrial problem: formulating the optimization problem, connecting different simulation tools and dealing with computationally expensive objective functions. The problem to be optimized is an air intake ventilation system of a tractor and consists of three computationally expensive objective functions. We describe the modeling of the system and its numerical evaluation with a commercial software. To obtain solutions in few function evaluations, a recently proposed surrogate-assisted evolutionary algorithm K-RVEA is applied. The diameters of four different outlets of the ventilation system are considered as decision variables. Fr…

ta1130209 industrial biotechnologyMathematical optimizationnumerical modelsOptimization problemlineaarinen optimointiLinear programmingComputer sciencesoftwarehydraulijärjestelmätventilationEvolutionary algorithmlinear programming02 engineering and technologyFunction (mathematics)Set (abstract data type)resistance020901 industrial engineering & automationhydraulic systemsilmanvaihto0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingShape optimizationoptimization
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Hierarchical control with virtual resistance optimization for efficiency enhancement and State-of-Charge balancing in DC microgrids

2015

This paper proposes a hierarchical control scheme which applies optimization method into DC microgrids in order to improve the system overall efficiency while considering the State-of-Charge (SoC) balancing at the same time. Primary droop controller, secondary voltage restoration controller and tertiary optimization tool formulate the complete hierarchical control system. Virtual resistances are taken as the decision variables for achieving the objective. simulation results are presented to verify the proposed approach.

EngineeringHierarchical controlLinear programmingbusiness.industryControl engineeringEfficiencyState-of-chargeSettore ING-IND/33 - Sistemi Elettrici Per L'Energiaefficiency genetic algorithm hierarchical control state-of-chargeState of chargeGenetic algorithmControl theoryGenetic algorithmHierarchical control systemSystem on a chipVoltage droopAlgorithm designbusiness2015 IEEE First International Conference on DC Microgrids (ICDCM)
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Best Proximity Points for Some Classes of Proximal Contractions

2013

Given a self-mapping g: A → A and a non-self-mapping T: A → B, the aim of this work is to provide sufficient conditions for the existence of a unique point x ∈ A, called g-best proximity point, which satisfies d g x, T x = d A, B. In so doing, we provide a useful answer for the resolution of the nonlinear programming problem of globally minimizing the real valued function x → d g x, T x, thereby getting an optimal approximate solution to the equation T x = g x. An iterative algorithm is also presented to compute a solution of such problems. Our results generalize a result due to Rhoades (2001) and hence such results provide an extension of Banach's contraction principle to the case of non-s…

Mathematical optimizationmetric spacesArticle SubjectIterative methodApplied Mathematicslcsh:MathematicsWork (physics)proximal contractionbest proximity pointExtension (predicate logic)Resolution (logic)lcsh:QA1-939Nonlinear programmingReal-valued functionPoint (geometry)Settore MAT/03 - GeometriaContraction principleAnalysisMathematicsAbstract and Applied Analysis
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The OptQuest Callable Library

2005

In this chapter we discuss the development and application of a library of functions that is the optimization engine for the OptQuest system. OptQuest is commercial software designed for optimizing complex systems, such as those formulated as simulation models. OptQuest has been integrated with several simulation packages with the goal of adding optimization capabilities. The optimization technology within OptQuest is based on the metaheuristic framework known as scatter search. In addition to describing the functionality of the OptQuest Callable Library (OCL) with an illustrative example, we apply it to a set of unconstrained nonlinear optimization problems.

Set (abstract data type)Commercial softwareMathematical optimizationComputer scienceComplex systemMetaheuristicCallable bondNonlinear programming
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A contribution to the linear programming approach to joint cost allocation: Methodology and application

2009

Abstract The linear programming (LP) approach has been commonly proposed for joint cost allocation purposes. Within a LP framework, the allocation rules are based on a marginal analysis. Unfortunately, the additivity property which is required to completely allocate joint costs fails in presence of capacity, institutional or environmental constraints. In this paper, we first illustrate that the non allocated part can be interpreted as a type of producer’s surplus. Then, by using the information contained in the Simplex tableau we propose an original two-stage methodology based on the marginal costs and the production elasticity of input factors to achieve an additive cost allocation pattern…

Marginal costMathematical optimizationCost allocationInformation Systems and ManagementSimplexGeneral Computer ScienceLinear programmingIterative methodManagement Science and Operations Researchcomputer.software_genreIndustrial and Manufacturing EngineeringExpert systemJoint costSimplex algorithmModeling and SimulationcomputerMathematicsEuropean Journal of Operational Research
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An optimality test for semi-infinite linear programming

1992

In this paper we present a test to characterize the optimal solutions for the continuous semi-infinite linear programming problem. This optimality characterization is a condition of Kuhn–Tucker type. The resolution of a linear program permits to check the optimality of a feasible point,to detect the unboundedness of the problem and to find descent directions. We give some illustrative examples. We show that the local Mangasarian–Fromovitz constraint qualification is almost equivalent to Slater qualification for this problem. Furthermore, it follows from our study that this optimality condition is always necessary for a wide class of semi-infinite linear programming problems

Constraint (information theory)Mathematical optimizationControl and OptimizationLinear programmingSemi-infiniteApplied MathematicsPoint (geometry)Management Science and Operations ResearchType (model theory)Semi-infinite programmingLinear-fractional programmingDescent (mathematics)MathematicsOptimization
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Continuous models combining slacks-based measures of efficiency and super-efficiency

2022

AbstractIn the framework of data envelopment analysis (DEA), Tone (Eur J Oper Res 130(3):498–509, 2001) introduced the slacks-based measure (SBM) of efficiency, which is a nonradial model that incorporates all the slacks of the evaluated decision-making units (DMUs) into their efficiency scores, unlike classical radial efficiency models. Next, Tone (Eur J Oper Res 143(1):32–41, 2002) developed the SBM super-efficiency model in order to differentiate and rank efficient DMUs, whose SBM efficiency scores are always 1. However, as pointed out by Chen (Eur J Oper Res 226(2):258–267, 2013), some interpretation problems arise when the so-called super-efficiency projections are weakly efficient, le…

nonlinear programmingsuper-inefficiencydata envelopment analysisUNESCO::CIENCIAS TECNOLÓGICASManagement Science and Operations Researchsuper-efficiencyCentral European Journal of Operations Research
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Scatter Search for the Point-Matching Problem in 3D Image Registration

2008

Scatter search is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, such as the surrogate constraint method, scatter search uses strategies for combining solution vectors that have proved effective in a variety of problem settings. We present a scatter-search implementation designed to find high-quality solutions for the 3D image-registration problem, which has many practical applications. This problem arises in computer vision applications when finding a correspondence or transformation …

education.field_of_studyComputer scienceHeuristic (computer science)business.industryPopulationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage registrationPoint set registrationMachine learningcomputer.software_genreEvolutionary computationNonlinear programmingRobustness (computer science)Artificial intelligenceeducationbusinessMetaheuristicAlgorithmcomputerINFORMS Journal on Computing
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