Difference between revisions of "Category:AMPL/TACO"

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This category lists all problems for which [http://www.ampl.org AMPL] code is provided that uses the TACO Toolkit for AMPL Control Optimization extensions. As AMPL does not support differential equations, the traditional approach has been to include finite-dimensional discretizations of the problem dynamics in the AMPL model.
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This category lists all problems for which [http://www.ampl.org AMPL] code is provided that uses the TACO Toolkit for AMPL Control Optimization extensions, compare <bib id="Kirches2011c" />. As AMPL does not support differential equations, the traditional approach has been to include finite-dimensional discretizations of the problem dynamics in the AMPL model.
 
TACO provides relief here by proposing a small set of extensions to the AMPL language that allows for easy and convenient modeling of ODE and DAE constraints as well as Bolza-type and least-squares-type objectives.
 
TACO provides relief here by proposing a small set of extensions to the AMPL language that allows for easy and convenient modeling of ODE and DAE constraints as well as Bolza-type and least-squares-type objectives.
  
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[[Category:Problem characterization]]
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[[Category: Implementation]]

Latest revision as of 10:00, 28 January 2016

This category lists all problems for which AMPL code is provided that uses the TACO Toolkit for AMPL Control Optimization extensions, compare [Kirches2011c]Author: C. Kirches; S. Leyffer
Journal: Mathematical Programming Computation
Number: 2
Pages: 227--265
Title: TACO -- A Toolkit for AMPL Control Optimization
Url: http://www.springerlink.com/openurl.asp?genre=article&id=doi:10.1007/s12532-013-0054-7
Volume: 5
Year: 2013
Link to Google Scholar
. As AMPL does not support differential equations, the traditional approach has been to include finite-dimensional discretizations of the problem dynamics in the AMPL model. TACO provides relief here by proposing a small set of extensions to the AMPL language that allows for easy and convenient modeling of ODE and DAE constraints as well as Bolza-type and least-squares-type objectives.

References

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