Search results for "optimization"

showing 10 items of 2824 documents

Modelling energy storage systems using Fourier analysis: An application for smart grids optimal management

2014

In this paper, a new and efficient model for variables representation, named F-coding, in optimal power dispatch problems for smart electrical distribution grids is proposed. In particular, an application devoted to optimal energy dispatch of Distributed Energy Resources including ideal storage devices is here considered. Electrical energy storage systems, such as any other component that must meet an integral capacity constraint in optimal dispatch problems, have to show the same energy level at the beginning and at the end of the considered timeframe for operation. The use of zero-integral functions, such as sinusoidal functions, for the synthesis of the charge and discharge course of bat…

Mathematical optimizationIntegral constraintMulti-objective evolutionary algorithmbusiness.industryComputer scienceFourier analysiEconomic dispatchSmart gridsMulti-objective optimizationEnergy storageElectrical energy storage systemSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicaSmart gridDistributed generationComponent (UML)Optimal dispatch of resourcebusinessRepresentation (mathematics)SoftwareEnergy (signal processing)Applied Soft Computing
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An ILS-Based Metaheuristic for the Stacker Crane Problem

2012

[EN] In this paper we propose a metaheuristic algorithm for the Stacker Crane Problem. This is an NP-hard arc routing problem whose name derives from the practical problem of operating a crane. Here we present a formulation and a lower bound for this problem and propose a metaheuristic algorithm based on the combination of a Multi-start and an Iterated Local Search procedures. Computational results on a large set of instances are presented.

Mathematical optimizationIterated local searchComputer scienceStackerComputerApplications_COMPUTERSINOTHERSYSTEMSMetaheuristicsUpper and lower boundsParallel metaheuristicDirected rural postman problemCombinatorial OptimizationCombinatorial optimizationLarge set (combinatorics)MATEMATICA APLICADAMetaheuristicArc routingAlgorithm
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Determining the Difficulty of Landscapes by PageRank Centrality in Local Optima Networks

2016

The contribution of this study is twofold: First, we show that we can predict the performance of Iterated Local Search (ILS) in different landscapes with the help of Local Optima Networks (LONs) with escape edges. As a predictor, we use the PageRank Centrality of the global optimum. Escape edges can be extracted with lower effort than the edges used in a previous study. Second, we show that the PageRank vector of a LON can be used to predict the solution quality (average fitness) achievable by ILS in different landscapes.

Mathematical optimizationIterated local searchbusiness.industrymedia_common.quotation_subject02 engineering and technologyMachine learningcomputer.software_genreLocal optima networkslaw.inventionGlobal optimumPageRanklaw020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingQuality (business)Artificial intelligencebusinessCentralitycomputerMathematicsmedia_common
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Two-level Schwarz method for unilateral variational inequalities

1999

The numerical solution of variational inequalities of obstacle type associated with second-order elliptic operators is considered. Iterative methods based on the domain decomposition approach are proposed for discrete obstacle problems arising from the continuous, piecewise linear finite element approximation of the differential problem. A new variant of the Schwarz methodology, called the two-level Schwarz method, is developed offering the possibility of making use of fast linear solvers (e.g., linear multigrid and fictitious domain methods) for the genuinely nonlinear obstacle problems. Namely, by using particular monotonicity results, the computational domain can be partitioned into (mes…

Mathematical optimizationIterative methodApplied MathematicsGeneral MathematicsDomain decomposition methodsFinite element methodPiecewise linear functionComputational MathematicsMultigrid methodVariational inequalityAdditive Schwarz methodApplied mathematicsSchwarz alternating methodMathematicsIMA Journal of Numerical Analysis
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The convergence of the perturbed Newton method and its application for ill-conditioned problems

2011

Abstract Iterative methods, such as Newton’s, behave poorly when solving ill-conditioned problems: they become slow (first order), and decrease their accuracy. In this paper we analyze deeply and widely the convergence of a modified Newton method, which we call perturbed Newton, in order to overcome the usual disadvantages Newton’s one presents. The basic point of this method is the dependence of a parameter affording a degree of freedom that introduces regularization. Choices for that parameter are proposed. The theoretical analysis will be illustrated through examples.

Mathematical optimizationIterative methodApplied MathematicsSteffensen's methodNewton's method in optimizationLocal convergenceComputational Mathematicssymbols.namesakeNonlinear systemNewton fractalSecant methodsymbolsNewton's methodMathematicsApplied Mathematics and Computation
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An Iterative Method for Pricing American Options Under Jump-Diffusion Models

2011

We propose an iterative method for pricing American options under jump-diffusion models. A finite difference discretization is performed on the partial integro-differential equation, and the American option pricing problem is formulated as a linear complementarity problem (LCP). Jump-diffusion models include an integral term, which causes the resulting system to be dense. We propose an iteration to solve the LCPs efficiently and prove its convergence. Numerical examples with Kou's and Merton's jump-diffusion models show that the resulting iteration converges rapidly.

Mathematical optimizationIterative methodValuation of optionsJump diffusionConvergence (routing)Finite difference methodFinite difference methods for option pricingLinear complementarity problemTerm (time)MathematicsSSRN Electronic Journal
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On properties of the iterative maximum likelihood reconstruction method

1989

In this paper, we continue our investigations6 on the iterative maximum likelihood reconstruction method applied to a special class of integral equations of the first kind, where one of the essential assumptions is the positivity of the kernel and the given right-hand side. Equations of this type often occur in connection with the determination of density functions from measured data. There are certain relations between the directed Kullback–Leibler divergence and the iterative maximum likelihood reconstruction method some of which were already observed by other authors. Using these relations, further properties of the iterative scheme are shown and, in particular, a new short and elementar…

Mathematical optimizationIterative proportional fittingIterative methodGeneral MathematicsKernel (statistics)Expectation–maximization algorithmGeneral EngineeringApplied mathematicsIterative reconstructionDivergence (statistics)Integral equationLocal convergenceMathematicsMathematical Methods in the Applied Sciences
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Scheduling shared continuous resources on many-cores

2014

We consider the problem of scheduling a number of jobs on m identical processors sharing a continuously divisible resource. Each job j comes with a resource requirement rj∈[0,1]. The job can be processed at full speed if granted its full resource requirement. If receiving only an x-portion of r_j, it is processed at an x-fraction of the full speed. Our goal is to find a resource assignment that minimizes the makespan (i.e., the latest completion time). Variants of such problems, relating the resource assignment of jobs to their processing speeds, have been studied under the term discrete-continuous scheduling. Known results are either very pessimistic or heuristic in nature. In this paper, …

Mathematical optimizationJob shop schedulingComputer scienceDistributed computingApproximation algorithmJob assignmentUnit sizeCompletion timeResource assignmentMultiprocessor schedulingScheduling (computing)Proceedings of the 26th ACM symposium on Parallelism in algorithms and architectures
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The distributed assembly permutation flowshop scheduling problem

2013

Nowadays, improving the management of complex supply chains is a key to become competitive in the twenty-first century global market. Supply chains are composed of multi-plant facilities that must be coordinated and synchronised to cut waste and lead times. This paper proposes a Distributed Assembly Permutation Flowshop Scheduling Problem (DAPFSP) with two stages to model and study complex supply chains. This problem is a generalisation of the Distributed Permutation Flowshop Scheduling Problem (DPFSP). The first stage of the DAPFSP is composed of f identical production factories. Each one is a flowshop that produces jobs to be assembled into final products in a second assembly stage. The o…

Mathematical optimizationJob shop schedulingStrategy and ManagementSupply chainESTADISTICA E INVESTIGACION OPERATIVANeighbourhood (graph theory)Management Science and Operations ResearchIndustrial and Manufacturing EngineeringDistributed assembly flowshopVariable neighborhood descentVariable (computer science)PermutationConstructive algorithmsKey (cryptography)ORGANIZACION DE EMPRESASProduction (computer science)Mathematics
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Due Dates and RCPSP

2006

Due dates are an essential feature of real projects, but little effort has been made in studying the RCPSP with due dates in the activities. This paper tries to bridge this gap by studying two problems: the TardinessRCPSP, in which the objective is total tardiness minimization and the DeadlineRCPSP, in which the due dates are strict (deadlines) and the objective is makespan minimization. The first problem is NP-hard and the second is much harder, since finding a feasible solution is already NP-hard. This paper has three objectives: Firstly to compare the performance on both problems of well-known RCPSP heuristics - priority rules, sampling procedures and metaheuristics - with new versions w…

Mathematical optimizationJob shop schedulingbusiness.industryComputer scienceTardinessProfitability indexMinificationProject managementbusinessHeuristicsMetaheuristicGenerator (mathematics)
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