Design Optimization Integrating the Outer Approximation Method with Process Simulators and Linear Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{deschaine:2002:FEA,
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author = "Larry M. Deschaine and Frank D. Francone",
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title = "Design Optimization Integrating the Outer
Approximation Method with Process Simulators and Linear
Genetic Programming",
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booktitle = "Proceedings of the 6th Joint Conference on Information
Science",
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year = "2002",
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editor = "H. John Caulfield and Shu-Heng Chen and
Heng-Da Cheng and Richard J. Duro and Vasant Honavar and
Etienne E. Kerre and Mi Lu and Manuel Grana Romay and
Timothy K. Shih and Dan Ventura and Paul P. Wang and
Yuanyuan Yang",
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pages = "618--621",
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address = "Research Triangle Park, North Carolina, USA",
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month = mar # " 8-13",
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publisher = "JCIS / Association for Intelligent Machinery, Inc.",
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bibsource = "DBLP, http://dblp.uni-trier.de",
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keywords = "genetic algorithms, genetic programming",
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ISBN = "0-9707890-1-7",
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URL = "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/deschaine/FEA_2002_Design_Optimization.pdf",
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abstract = "Fast process optimisation is a challenge. Processes
are often complex and the intricate simulators written
to solve them can take hours or days per simulation to
run. Optimization techniques that require many calls to
a simulator can take days or months to solve. While
advances in optimisation algorithms, such as the outer
approximation method have reduced the solution time by
a factor of ten or more when compared to other methods,
long solutions times still can occur. This work
explores the development of simulating a simulator to
enable optimal solution development in an accelerated
time frame. The technique used to develop the simulated
simulator is linear genetic programming (LGP). LGP
approximated a complex industrial process simulator
that took hours to execute per run with a high fitness
program - applied (testing) data set R2 fitness of
0.989. The LGP solution executes in less than a second.
This success opens up the possibility of optimising
functions faster using these LGP derived high fitness
simulator approximations. Since the LGP simulated
process simulator now executes in less than a second,
as opposed to hours, using an intensive multiple call
optimisation technique such as genetic algorithms and
evolutionary strategies is now also feasible.",
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notes = "
FEA2002 In conjunction with Sixth Joint Conference on
Information Sciences
My printer refuses to deal with this as PDF",
- }
Genetic Programming entries for
Larry M Deschaine
Frank D Francone
Citations