Search results for "optimization"

showing 10 items of 2824 documents

A Perturbation Approach to Continuous-Time Portfolio Selection Under Stochastic Investment Opportunities

2013

This paper studies portfolio selection in continuous-time models with stochastic investment opportunities. We consider asset allocation problems where preferences are specified as power utility derived from terminal wealth as well as consumption-savings problems with recursive utility Epstein-Zin preferences. The paper approximates the associated dynamic programming problem by perturbing the coefficients of the stochastic dynamics. We represent the Hamilton-Jacobi-Bellman equation as a series of partial differential equations that can be solved iteratively in closed-form through computer algebra software, at any desired accuracy.

Power utilityMathematical optimizationPartial differential equationbusiness.industryMathematicsofComputing_NUMERICALANALYSISPerturbation (astronomy)Asset allocationSymbolic computationDynamic programmingSoftwareComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATIONEconomicsPortfoliobusinessSSRN Electronic Journal
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A predictive function optimization algorithm for multi-spectral skin lesion assessment

2015

The newly introduced Kubelka-Munk Genetic Algorithm (KMGA) is a promising technique used in the assessment of skin lesions. Unfortunately, this method is computationally expensive due to its function inverting process. In the work of this paper, we design a Predictive Function Optimization Algorithm in order to improve the efficiency of KMGA by speeding up its convergence rate. Using this approach, a High-Convergence-Rate KMGA (HCR-KMGA) is implemented onto multi-core processors and FPGA devices respectively. Furthermore, the implementations are optimized using parallel computing techniques. Intensive experiments demonstrate that HCR-KMGA can effectively accelerate KMGA method, while improv…

Predictive functionRate of convergenceOptimization algorithmComputer scienceGenetic algorithmProcess (computing)Function (mathematics)Parallel computingField-programmable gate arraySkin lesionAlgorithm2015 23rd European Signal Processing Conference (EUSIPCO)
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DECISION-MAKING MODELS FOR PREDICTIVE MAINTENANCE SERVICE SUPPORT SYSTEMS

2023

Nell'era digitale, la tecnologia è in continua evoluzione, con enormi progressi nell'automazione che consentono una gestione della manutenzione più efficiente ed economica. Le tecnologie digitali stanno convergendo e avanzando insieme alle industrie, determinando progressi significativi nella gestione della manutenzione. La tradizionale strategia di manutenzione preventiva gestita dall'uomo lascia progressivamente spazio alla manutenzione predittiva, che rappresenta un’ottima opportunità per migliorare significativamente la pianificazione della manutenzione del sistema, in particolare per i sistemi più complessi e dal significativo valore monetario. Tuttavia, l’implementazione di tecniche d…

Predictive maintenance Decision-making models complex systems optimization maintenance digitalization maintenance management Industry 4.0 Multi-criteria decision-making Complex systemsSettore ING-IND/17 - Impianti Industriali Meccanici
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Preoperative Planning for Guidewires Employing Shape-Regularized Segmentation and Optimized Trajectories

2019

Upcoming robotic interventions for endovascular procedures can significantly reduce the high radiation exposure currently endured by surgeons. Robotically driven guidewires replace manual insertion and leave the surgeon the task of planning optimal trajectories based on segmentation of associated risk structures. However, such a pipeline brings new challenges. While Deep learning based segmentation such as U-Net can achieve outstanding Dice scores, it fails to provide suitable results for trajectory planning in annotation scarce environments. We propose a preoperative pipeline featuring a shape regularized U-Net that extracts coherent anatomies from pixelwise predictions. It uses Rapidly-ex…

Preoperative planningComputer sciencebusiness.industryDeep learningPipeline (computing)DiceMachine learningcomputer.software_genreTask (project management)Convex optimizationSegmentationArtificial intelligenceMotion planningbusinesscomputer
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Coherence Checking and Propagation of Lower Probability Bounds

2003

In this paper we use imprecise probabilities, based on a concept of generalized coherence (g-coherence), for the management of uncertain knowledge and vague information. We face the problem of reducing the computational difficulties in g-coherence checking and propagation of lower conditional probability bounds. We examine a procedure, based on linear systems with a reduced number of unknowns, for the checking of g-coherence. We propose an iterative algorithm to determine the reduced linear systems. Based on the same ideas, we give an algorithm for the propagation of lower probability bounds. We also give some theoretical results that allow, by suitably modifying our algorithms, the g-coher…

Probability boxMathematical optimizationSettore MAT/06 - Probabilita' E Statistica MatematicaPosterior probabilitynon relevant gainLaw of total probabilityConditional probabilitybasic setsbasic sets; basic sets.; g-coherence checking; lower conditional probability bounds; non relevant gains; propagationCoherence (statistics)Conditional probability distributiong-coherence checking; lower conditional probability bounds; non relevant gainsImprecise probabilityTheoretical Computer Sciencelower conditional probability boundRegular conditional probabilitynon relevant gainspropagationlower conditional probability boundsGeometry and Topologyg-coherence checkingSoftwareMathematics
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Modelling and optimization of modular system for power generation from a salinity gradient

2019

Abstract Pressure retarded osmosis has been proposed for power generation from a salinity gradient resource. The process has been promoted as a promising technology for power generation from renewable resources, but most of the experimental work has been done on a laboratory size units. To date, pressure retarded osmosis optimization and operation is based on parametric studies performed on laboratory scale units, which leaves a gap in our understanding of the process behaviour in a full-scale modular system. A computer model has been developed to predict the process performance. Process modelling was performed on a full-scale membrane module and impact of key operating parameters such as h…

Process modeling060102 archaeologyRenewable Energy Sustainability and the Environmentbusiness.industry020209 energyPressure-retarded osmosisProcess (computing)06 humanities and the arts02 engineering and technologyOsmosisRenewable energyMembrane technologyElectricity generation0202 electrical engineering electronic engineering information engineeringEnvironmental science0601 history and archaeologyProcess optimizationbusinessProcess engineeringRenewable Energy
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Economic lot scheduling on multiple production lines with resource constraints

2003

Abstract This paper deals with the multiple production line economic lot scheduling problem, where some items cannot be produced concurrently since they compete for some discrete resources. In particular, cyclic schedules are sought for a problem where identical production lines are present, lost sales are allowed, and minimization of the long-range production, setup, inventory, and shortage penalty costs are required. A heuristic procedure for this problem is introduced, a numerical example is worked out and some computational experiments are presented.

Production lineEconomics and EconometricsMathematical optimizationResource constraintsScheduling (production processes)Management Science and Operations ResearchGeneral Business Management and AccountingIndustrial and Manufacturing EngineeringEconomic lot scheduling problemFair-share schedulingGenetic algorithm schedulingEconomicsMinificationHeuristicsInternational Journal of Production Economics
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The linear saturated decentralized strategy for constrained flow control is asymptotically optimal

2013

We present an algorithm for constrained network flow control in the presence of an unknown demand. Our algorithm is decentralized in the sense that it is implemented by a team of agents, each controlling just the flow on a single arc of the network based only on the buffer levels at the nodes at the extremes of the arc, while ignoring the actions of other agents and the network topology. We prove that our algorithm is also stabilizing and steady-state optimal. Specifically, we show that it asymptotically produces the minimum-norm flow. We finally generalize our algorithm to networks with a linear dynamics and we prove that certain least-square optimality properties still hold.

Production-distribution systemsOptimizationMathematical optimizationRobust controlUncertain systemsMinimum normNetwork topologyMinimum norm flowControl theoryElectric network topologyConstrained flowUncertain systemsElectrical and Electronic EngineeringMathematicsFlow control (data)Network topologyAsymptotically optimalRobust control; OptimizationUncertain systemEthernet flow controlAsymptotically optimal Constrained flow Distributed flow control Minimum norm Network optimization Network topology Production-distribution systems Steady-state optimal; Algorithms Electric network topology Flow control Uncertain systems; OptimizationProduction-distribution systemFlow controlAsymptotically optimal algorithmControl and Systems EngineeringSteady-state optimalMinimum-cost flow problemDistributed flow controlRobust controlNetwork optimization; Distributed flow control; Production-distribution systems; Uncertain systems; Minimum norm flowNetwork optimizationAlgorithms
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Justification technique generalizations

2006

The justification technique was introduced various decades ago for the resource-constrained project scheduling problem, although it has rarely been used with the problem. Justification is a simple and quick technique which when applied to schedules produces a new schedule that is, at most, as long as the original schedule — and often shorter. A recent article (Valls et al, 2005), showed that incorporating justification in heuristic algorithms can produce a substancial improvement in the results obtained. These results have motivated us to generalise this technique in order to study it in greater depth. This paper proposes distinct forms and generalisations for the justification technique an…

Project scheduling problemScheduleMathematical optimizationRelation (database)Computer scienceHeuristicAlgorithmic efficiencyHeuristicsSimple (philosophy)
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A practical protocol for calibration of nutrient removal wastewater treatment models

2011

Activated sludge models can be very useful for designing and managing wastewater treatment plants (WWTPs). However, as with every model, they need to be calibrated for correct and reliable application. Activated sludge model calibration is still a crucial point that needs appropriate guidance. Indeed, although calibration protocols have been developed, the model calibration still represents the main bottleneck to modelling. This paper presents a procedure for the calibration of an activated sludge model based on a comprehensive sensitivity analysis and a novel step-wise Monte Carlo-based calibration of the subset of influential parameters. In the proposed procedure the complex calibration i…

Protocol (science)Atmospheric ScienceEngineeringMathematical optimizationSettore ICAR/03 - Ingegneria Sanitaria-AmbientaleCalibration (statistics)business.industryMonte Carlo methodsensitivity analysiActivated sludge modelidentifiabilityGeotechnical Engineering and Engineering Geologycalibration protocolGLUEBottleneckASMIdentifiabilitySensitivity (control systems)businessGLUEwastewater treatment modellingSimulationCivil and Structural EngineeringWater Science and TechnologyJournal of Hydroinformatics
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