Computational experience with generalized simulated annealing over continuous variables

Daniel G. Brooks; William A. Verdini

doi:10.1080/01966324.1988.10737248

Computational experience with generalized simulated annealing over continuous variables

Daniel G. Brooks, William A. Verdini

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

Stochastic optimization procedures have been shown to be efficient methods for finding global extrema of objective functions. In this article we report computational results obtained using the generalized simulated annealing method on a set of standard global optimization test problems. The results are compared to those obtained using the best known competing stochastic optimization methods.

Original language	English (US)
Pages (from-to)	425-449
Number of pages	25
Journal	American Journal of Mathematical and Management Sciences
Volume	8
Issue number	3-4
DOIs	https://doi.org/10.1080/01966324.1988.10737248
State	Published - Jan 1 1988

Keywords

Annealing
Global optimization
Stochastic optimization

ASJC Scopus subject areas

Business, Management and Accounting(all)
Applied Mathematics

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10.1080/01966324.1988.10737248

Cite this

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title = "Computational experience with generalized simulated annealing over continuous variables",

abstract = "Stochastic optimization procedures have been shown to be efficient methods for finding global extrema of objective functions. In this article we report computational results obtained using the generalized simulated annealing method on a set of standard global optimization test problems. The results are compared to those obtained using the best known competing stochastic optimization methods.",

keywords = "Annealing, Global optimization, Stochastic optimization",

author = "Brooks, {Daniel G.} and Verdini, {William A.}",

year = "1988",

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T1 - Computational experience with generalized simulated annealing over continuous variables

AU - Brooks, Daniel G.

AU - Verdini, William A.

PY - 1988/1/1

Y1 - 1988/1/1

N2 - Stochastic optimization procedures have been shown to be efficient methods for finding global extrema of objective functions. In this article we report computational results obtained using the generalized simulated annealing method on a set of standard global optimization test problems. The results are compared to those obtained using the best known competing stochastic optimization methods.

AB - Stochastic optimization procedures have been shown to be efficient methods for finding global extrema of objective functions. In this article we report computational results obtained using the generalized simulated annealing method on a set of standard global optimization test problems. The results are compared to those obtained using the best known competing stochastic optimization methods.

KW - Annealing

KW - Global optimization

KW - Stochastic optimization

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JF - American Journal of Mathematical and Management Sciences

SN - 0196-6324

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ER -

Computational experience with generalized simulated annealing over continuous variables

Abstract

Keywords

ASJC Scopus subject areas

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