Generalized Simulated Annealing for Function Optimization

Bohachevsky, I.O.; Johnson, Mark E.; Stein, M. L.

doi:10.1080/00401706.1986.10488128

Cited by 324 publications

(175 citation statements)

References 13 publications

Supporting

Mentioning

165

Contrasting

Unclassified

Order By: Relevance

“…with a fixed parameter θ, the χ 2 n of the previously accepted step, and the χ 2 * of the global optimum (Bohachevsky et al 1986;Locatelli 2000). The latter value is typically unknown and one has to resort to a lower bound or sensible approximation for χ 2 * like the χ 2 of the current best-fit of an individual run.…”

Section: Simulated Annealingmentioning

confidence: 99%

The circumstellar disk of HH 30

Madlener

Wolf

Dutrey

et al. 2012

A&A

View full text Add to dashboard Cite

Context. Circumstellar disks are characteristic for star formation and vanish during the first few Myr of stellar evolution. During this time planets are believed to form in the dense midplane by growth, sedimentation and aggregation of dust. Indicators of disk evolution, such as holes and gaps, can be traced in the spectral energy distribution (SED) and spatially resolved images. Aims. We aim to construct a self-consistent model of HH 30 by fitting all available continuum observations simultaneously. New data sets not available in previous studies, such as high-resolution interferometric imaging with the Plateau de Bure Interferometer (PdBI) at λ = 1.3 mm and SED measured with IRS on the Spitzer Space Telescope in the mid-infrared, put strong constraints on predictions and are likely to provide new insights into the evolutionary state of this object. Methods. A parameter study based on simulated annealing was performed to find unbiased best-fit models for independent observations made in the wavelength domain λ ∼ 1 μm . . . 4 mm. The method essentially creates a Markov chain through parameter space by comparing predictions generated by our self-consistent continuum radiation transfer code MC3D with observations. Results. We present models of the edge-on circumstellar disk of HH 30 based on observations from the near-infrared to mmwavelengths that suggest the presence of an inner depletion zone with ∼45 AU radius and a steep decline of mm opacity beyond 140 AU. Our modeling indicates that several modes of dust evolution such as growth, settling, and radial migration are taking place in this object. Conclusions. High-resolution observations of HH 30 at different wavelengths with next-generation observatories such as ALMA and JWST will enable the modeling of inhomogeneous dust properties and significantly expand our understanding of circumstellar disk evolution.

show abstract

Section: Simulated Annealingmentioning

confidence: 99%

The circumstellar disk of HH 30

Madlener

Wolf

Dutrey

et al. 2012

A&A

View full text Add to dashboard Cite

show abstract

“…They include adaptive random search [Pronzato et al (1984)], genetic algorithms [Goldberg (1989)], the filled function method [Renpu (1990)], multi level methods [Kan and Timmer (1987)] and a method using stochastic differential equations [Aluffi-Pentini et al (1988)]. Both Vanderbilt et al (1984) and Bohachevsky et al (1986) have modified simulated annealing for continuous variable problems.…”

Section: B Simulated Annealing For Continuous Variable Problemsmentioning

confidence: 99%

Global optimization of statistical functions with simulated annealing

Goffe

Ferrier

Rogers

1994

Journal of Econometrics

1,408

832

View full text Add to dashboard Cite

“…This algorithm is a set of rules for searching large solution spaces in a manner that mimics the annealing process of metals. The algorithm simulates the behavior of an ensemble of atoms in equilibrium at a given finite temperature and its original framework can be traced to Metropolis [14]. This algorithm has been regularly used in global function optimisation and statistical applications.…”

Section: B Simulated Annealing (Sa)mentioning

confidence: 99%

Continuous Stirred Tank Reactor Optimisationvia Simulated Annealing, Firefly and Ant ColonyOptimisation Elements on the Steepest Ascent

Luangpaiboon¹

2011

IJMLC

View full text Add to dashboard Cite

Abstract-The objective of this work is to make use of conventional response surface methodologies and basic elements from metaheuristic algorithms in the design of influential variables for engineering systems. A method of steepest ascent and its integrated approaches with simulated annealing, firefly and ant colony optimisation algorithms, are compared on a simulated continuous stirred tank reactor or CSTR with various levels of signal noise. These metaheuristics contain the complicatedness in terms of their parameters. An additional series of computational experiments were conducted and analysed in terms of the minimax and mean squared error performance measures including Taguchi's signal to noise ratio. Proper levels of these parameters are analysed to recommend the best parameter choices. On the experimental results of all the algorithms with the preferable levels of parameters, the method of steepest ascent seems to be the most efficient on the CSTR surface at the lower levels of noise. However, the integrated approaches with all simulated annealing, firefly and ant colony optimisation elements work well when the standard deviation of the noise is at higher levels. Although the average, the standard deviation of the greatest actual concentration of the product and percentage of sequences ended at the optimum from the integrated algorithms with simulated annealing and ant colony optimisation seem to be better, they need more average design points, especially with ant colony optimisation element, to converge to the optimum when compared.

show abstract

Generalized Simulated Annealing for Function Optimization

Cited by 324 publications

References 13 publications

The circumstellar disk of HH 30

The circumstellar disk of HH 30

Global optimization of statistical functions with simulated annealing

Continuous Stirred Tank Reactor Optimisationvia Simulated Annealing, Firefly and Ant ColonyOptimisation Elements on the Steepest Ascent

Contact Info

Product

Resources

About