Nonlinear Programming with Pyomo

Michael L. Bynum, Gabriel A. Hackebeil, William E. Hart, Carl D. Laird, Bethany L. Nicholson, John D. Siirola, Jean-Paul Watson and David L. Woodruff
Additional contact information
Michael L. Bynum: Sandia National Laboratories
Gabriel A. Hackebeil: Deepfield Nokia
William E. Hart: Sandia National Laboratories
Carl D. Laird: Sandia National Laboratories
Bethany L. Nicholson: Sandia National Laboratories
John D. Siirola: Sandia National Laboratories
Jean-Paul Watson: Lawrence Livermore National Laboratory
David L. Woodruff: University of California

Chapter Chapter 7 in Pyomo — Optimization Modeling in Python, 2021, pp 91-109 from Springer

Abstract: Abstract This chapter describes the nonlinear programming capabilities of Pyomo. It presents the nonlinear expressions and functions supported, and it provides some tips for formulating and solving nonlinear programming problems. This chapter also provides several real-world examples to illustrate formulating and solving nonlinear programming problems. Finally, it provides a brief discussion of supported solvers for nonlinear problems.

Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (1)

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:978-3-030-68928-5_7

Ordering information: This item can be ordered from
http://www.springer.com/9783030689285

DOI: 10.1007/978-3-030-68928-5_7

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 ().