Mathematical Modeling and Optimization
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 2 in Pyomo — Optimization Modeling in Python, 2017, pp 15-27 from Springer
Abstract:
Abstract This chapter provides a primer on optimization and mathematical modeling. It does not provide a complete description of these topics. Instead, this chapter provides enough background information to support reading the rest of the book. For more discussion of optimization modeling techniques see, for example, Williams [86]. Implementations of simple examples of models are shown to provide the reader with a quick start to using Pyomo.
Keywords: Decision Variable; Problem Instance; Linear Expression; Nonlinear Optimization Model; Happiness Function (search for similar items in EconPapers)
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_2
Ordering information: This item can be ordered from
http://www.springer.com/9783319588216
DOI: 10.1007/978-3-319-58821-6_2
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 ().