Search results for "Penalty function"

showing 3 items of 3 documents

Regularized pseudopotential for mean-field calculations

2019

We present preliminary results obtained with a finite-range two-body pseudopotential complemented with zero-range spin-orbit and density-dependent terms. After discussing the penalty function used to adjust parameters, we discuss predictions for binding energies of spherical nuclei calculated at the mean-field level, and we compare them with those obtained using the standard Gogny D1S finite-range effective interaction.

HistoryNuclear Theory[PHYS.NUCL]Physics [physics]/Nuclear Theory [nucl-th]Binding energyNuclear TheoryFOS: Physical sciencesSpin orbitsMean-field calculationsBinding energy01 natural sciences114 Physical sciencesEducationPseudopotentialNuclear Theory (nucl-th)Effective interactions0103 physical sciencesDensity dependentPenalty method010306 general physicsNuclear theoryPseudopotentialsPhysics010308 nuclear & particles physicsPhysicstiheysfunktionaaliteoriaPenalty functionComputer Science ApplicationsMean field theoryDensity dependentQuantum electrodynamicsydinfysiikkaMean-field level
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A penalty-based edge assembly memetic algorithm for the vehicle routing problem with time windows

2010

In this paper, we present an effective memetic algorithm for the vehicle routing problem with time windows (VRPTW). The paper builds upon an existing edge assembly crossover (EAX) developed for the capacitated VRP. The adjustments of the EAX operator and the introduction of a novel penalty function to eliminate violations of the time window constraint as well as the capacity constraint from offspring solutions generated by the EAX operator have proven essential to the heuristic's performance. Experimental results on Solomon's and Gehring and Homberger benchmarks demonstrate that our algorithm outperforms previous approaches and is able to improve 184 best-known solutions out of 356 instance…

Mathematical optimizationSDG 16 - PeaceGeneral Computer ScienceHeuristic (computer science)EconomicsSDG 16 - Peace Justice and Strong InstitutionsCrossoverMemetic algorithmManagement Science and Operations ResearchEAX mode/dk/atira/pure/sustainabledevelopmentgoals/peace_justice_and_strong_institutionsPenalty functionVehicle routingJustice and Strong InstitutionsModeling and SimulationVehicle routing problemMemetic algorithmPenalty methodEnhanced Data Rates for GSM EvolutionRouting (electronic design automation)AlgorithmTime windowsMathematicsComputers and Operations Research
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Variable Selection with Quasi-Unbiased Estimation: the CDF Penalty

2022

We propose a new non-convex penalty in linear regression models. The new penalty function can be considered a competitor of the LASSO, SCAD or MCP penalties, as it guarantees sparse variable selection while reducing bias for the non-null estimates. We introduce the methodology and present some comparisons among different approaches.

Variable selection non-convex penalty function LASSO SCAD MCP
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