Differential Algebraic Equations
William E. Hart,
Carl D. Laird,
Jean-Paul Watson,
David L. Woodruff,
Gabriel A. Hackebeil,
Bethany L. Nicholson and
John D. Siirola
Additional contact information
William E. Hart: Sandia National Laboratories
Carl D. Laird: Sandia National Laboratories
Jean-Paul Watson: Sandia National Laboratories
David L. Woodruff: University of California, Davis
Gabriel A. Hackebeil: University of Michigan
Bethany L. Nicholson: Sandia National Laboratories
John D. Siirola: Sandia National Laboratories
Chapter Chapter 11 in Pyomo — Optimization Modeling in Python, 2017, pp 201-209 from Springer
Abstract:
Abstract This chapter documents how to formulate and solve optimization problems with differential and algebraic equations (DAEs). The pyomo.dae package allows users to easily incorporate detailed dynamic models within an optimization framework and is flexible enough to represent a wide variety of differential equations. We also demonstrate several automated solution techniques included in pyomo.dae that apply a simultaneous discretization approach to solve dynamic optimization problems.
Date: 2017
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-58821-6_11
Ordering information: This item can be ordered from
http://www.springer.com/9783319588216
DOI: 10.1007/978-3-319-58821-6_11
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().