Search results for "Optimization problem"

showing 10 items of 281 documents

Longest Common Subsequence from Fragments via Sparse Dynamic Programming

1998

Sparse Dynamic Programming has emerged as an essential tool for the design of efficient algorithms for optimization problems coming from such diverse areas as Computer Science, Computational Biology and Speech Recognition [7,11,15]. We provide a new Sparse Dynamic Programming technique that extends the Hunt-Szymanski [2,9,8] paradigm for the computation of the Longest Common Subsequence (LCS) and apply it to solve the LCS from Fragments problem: given a pair of strings X and Y (of length n and m, resp.) and a set M of matching substrings of X and Y, find the longest common subsequence based only on the symbol correspondences induced by the substrings. This problem arises in an application t…

Dynamic programmingCombinatoricsSet (abstract data type)Longest common subsequence problemOptimization problemMatching (graph theory)Combinatorial optimizationData structureSubstringMathematics
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Solving multiobjective optimization problems with decision uncertainty: an interactive approach

2018

We propose an interactive approach to support a decision maker to find a most preferred robust solution to multiobjective optimization problems with decision uncertainty. A new robustness measure that is understandable for the decision maker is incorporated as an additional objective in the problem formulation. The proposed interactive approach utilizes elements of the synchronous NIMBUS method and is aimed at supporting the decision maker to consider the objective function values and the robustness of a solution simultaneously. In the interactive approach, we offer different alternatives for the decision maker to express her/his preferences related to the robustness of a solution. To conso…

Economics and EconometricsMathematical optimization050208 financerobust solutionsComputer science05 social sciencesmultiple criteria decision makinginteractive methodsDecision makerNIMBUSmonitavoiteoptimointiVisualizationMultiobjective optimization problemRobustness (computer science)0502 economics and businesshandling uncertaintiesrobustness measureBusiness and International Management050203 business & managementJournal of Business Economics
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A model for designing callable bonds and its solution using tabu search

1997

Abstract We formulate the problem of designing callable bonds as a non-linear, global, optimization problem. The data of the model are obtained from simulations of holding-period returns of a given bond design, which are used to compute a certainty equivalent return, viz., some target assets. The design specifications of the callable bond are then adjusted so that the certainty equivalent return is maximized. The resulting problem is multi-modal, and a tabu search procedure, implemented on a distributed network of workstations, is used to optimize the bond design. The model is compared with the classical portfolio immunization model, and the tabu search solution technique is compared with s…

Economics and EconometricsMathematical optimizationControl and OptimizationOptimization problemApplied MathematicsImmunization (finance)Tabu searchCallable bondTabu searchCallable bondsProduct designParallel computationsSimulated annealingEconomicsPortfolioFinancial innovationHill climbingGlobal optimizationSimulation
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A problem-adjusted genetic algorithm for flexibility design

2013

Many present markets for goods and services have highly volatile demand due to short life cycles and strong competition in saturated environments. Determination of capacity levels is difficult because capacities often need to be set long before demand realizes. In order to avoid capacity-demand mismatches, operations managers employ mix-flexible resources which allow them to shift excess demands to unused capacities. The Flexibility Design Problem (FDP) models the decision on the optimal configuration of a flexible (manufacturing) network. FDP is a difficult stochastic optimization problem, for which traditional exact approaches are not able to solve but the smallest instances in reasonable…

Economics and EconometricsMathematical optimizationSDG 16 - PeaceComputer scienceMetaheuristicsManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringStochastic optimization problemGenetic algorithmLocal search (optimization)/dk/atira/pure/sustainabledevelopmentgoals/industry_innovation_and_infrastructureNetwork designInnovationMetaheuristicFlexibility (engineering)business.industrySDG 16 - Peace Justice and Strong InstitutionsFlexibility designSolver/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsGeneral Business Management and AccountingFlexible manufacturingJustice and Strong InstitutionsGenetic algorithmSimulated annealingChainingand InfrastructureStochastic optimizationSDG 9 - Industry Innovation and InfrastructurebusinessSDG 9 - IndustryInternational Journal of Production Economics
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A naïve approach to speed up portfolio optimization problem using a multiobjective genetic algorithm

2012

a b s t r a c t Genetic algorithms (GAs) are appropriate when investors have the objective of obtaining mean-variance (VaR) efficient frontier as minimising VaR leads to non-convex and non-differential risk-return optimisation problems. However GAs are a time-consuming optimisation technique. In this paper, we propose to use a naive approach consisting of using samples split by quartile of risk to obtain complete efficient frontiers in a reasonable computation time. Our results show that using reduced problems which only consider a quartile of the assets allow us to explore the efficient frontier for a large range of risk values. In particular, the third quartile allows us to obtain efficie…

Economics and EconometricsMathematical optimizationSpeedupAlgoritmo genéticoComputer scienceStrategy and ManagementComputationValue‑at‑RiskLarge rangelcsh:BusinessValue¿at¿Riskddc:650Genetic algorithmEconometricsG11Business and International ManagementMarketingValue-at-RiskEfficient frontierQuartileEfficient portfolioGenetic algorithmValor en riesgovalue.at.RiskC81Portfolio optimization problemlcsh:HF5001-6182Cartera eficienteLENGUAJES Y SISTEMAS INFORMATICOS
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Special functions for the study of economic dynamics: The case of the Lucas-Uzawa model

2008

The special functions are intensively used in mathematical physics to solve differential systems. We argue that they should be most useful in economic dynamics, notably in the assessment of the transition dynamics of endogenous economic growth models. We illustrate our argument on the famous Lucas-Uzawa model, which we solve by the means of Gaussian hypergeometric functions. We show how the use of Gaussian hypergeometric functions allows for an explicit representation of the equilibrium dynamics of all variables in level. The parameters of the involved hypergeometric functions are identified using the Pontryagin conditions arising from the underlying optimization problems. In contrast to th…

Economics and EconometricsOptimization problemApplied MathematicsDimensionality reductionGaussianContrast (statistics)Optimal controlsymbols.namesakeSpecial functionssymbolsApplied mathematicsHypergeometric functionRepresentation (mathematics)MathematicsJournal of Mathematical Economics
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Passive congregation based particle swam optimization (pso) with self-organizing hierarchical approach for non-convex economic dispatch

2017

This paper proposes a passive congregation based PSO with self-organizing hierarchical algorithm approach for solving the economic dispatch problem of power system, where some of the units have prohibited operating zones. This Algorithm is known to perform better than conventional gradient based optimization methods for non-convex optimization problems. Conventional PSO algorithm is a population based heuristic search, employing problem of premature convergence. In this work, an innovative approach based on the concept of passive congregation based PSO with self-organizing hierarchical approach is employed to overcome the problem of premature convergence in classical PSO method.

Electric power systemMathematical optimizationOptimization problemConvergence (routing)MathematicsofComputing_NUMERICALANALYSISRegular polygonEconomic dispatchParticle swarm optimizationPremature convergenceHierarchical algorithm2017 2nd International Conference on Power and Renewable Energy (ICPRE)
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Optimization of the domain in elliptic variational inequalities

1988

This paper is concerned with a nonsmooth shape optimization problem for the Signorini unilateral boundary-value problem. The necessary optimality conditions are derived. The results of computations are presented.

Elliptic curveMathematical optimizationControl and OptimizationApplied MathematicsComputationVariational inequalityShape optimization problemBoundary value problemGradient methodFinite element methodDomain (mathematical analysis)MathematicsApplied Mathematics & Optimization
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Electromagnetic optimization of passive RFID sensor nodes

2012

RFID passive tags are nowadays starting to be considered more than labeling devices: by properly analyzing the two-ways communication link it is possible to get information about the state of a tagged object, without any specific embedded sensor or local power supply. Despite of the generality and the straightforwardness of the approach, the design of such a class of devices requires specific strategies to make the radio-sensors able to properly track the evolution of the phenomena under observation, jointly optimizing communication and sensing requirements. In this paper the optimization problem is formalized by means of convenient matching charts and evaluated in realistic experimental ex…

EngineeringGeneralityClass (computer programming)Optimization problemMatching (graph theory)business.industryReal-time computingTrack (rail transport)Object (computer science)Power (physics)Electronic engineeringState (computer science)businessrifd antenna design2012 6th European Conference on Antennas and Propagation (EUCAP)
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ECONOMIC-STATISTICAL DESIGN APPROACH FOR A VSSI X-BAR CHART CONSIDERING TAGUCHI LOSS FUNCTION AND RANDOM PROCESS SHIFTS

2014

Economic design approaches of control charts are commonly based on the assumption that various cost parameters values and the occurrence risk of assignable causes have to be a priori known with precision. However, in real operative contexts, such parameters can be really difficult to accurately estimate, especially considering costs arising from out-of-control conditions of the process. As consequence, pure economic design approaches can involve chart schemes with low statistical performance. To overcome such limitation, it is herein proposed a multi-objective economic-statistical design approach for an adaptive X-bar chart. In particular, such approach aims at the minimization of both the…

EngineeringMathematical optimizationGeneral Computer Sciencebusiness.industryStochastic processEnergy Engineering and Power TechnologyAerospace Engineeringmulti-objective optimization problemStatistical process controlIndustrial and Manufacturing Engineeringadaptive X-bar control chartNuclear Energy and EngineeringChartControl chartTaguchi loss functionStatistical process controlSensitivity (control systems)ε-constraint methodElectrical and Electronic EngineeringSafety Risk Reliability and QualitybusinessRandom variableSettore ING-IND/16 - Tecnologie E Sistemi Di Lavorazione\bar x and R chart
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