Springer Optimization and Its Applications

Pyomo — Optimization Modeling in Python

Authors: Hart, W.E., Laird, C.D., Watson, J.-P., Woodruff, D.L., Hackebeil, G.A., Nicholson, B.L., Siirola, J.D.

  • ​​Unique book describing the user-friendly Pyomo modeling tool, the most comprehensive open source modeling software that can model linear programs, integer programs, nonlinear programs, stochastic programs and disjunctive programs
  • Second edition present additional PYOMO capabilities not appearing in other sources
  • Discusses Pyomo's modeling components, illustrated with extensive examples 
  • Introduces beginners to the software and presents chapters for advanced modeling capabilities​
  • Contains a comprehensive tutorial
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  • ISBN 978-3-319-58821-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
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  • ISBN 978-3-319-58819-3
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About this Textbook

​This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming.

Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.

About the authors

William E. Hart, Jean-Paul Watson, Carl D. Laird, Bethany L. Nicholson, and John D. Siirola are researchers affiliated with the Sandia National Laboratories in Albuquerque, New Mexico. David Woodruff is professor is the graduate school of management at the University of California, Davis. Gabriel Hackebeil is a math programming consultant at the University of Michigan.

Table of contents (14 chapters)

  • Introduction

    Hart, William E. (et al.)

    Pages 1-11

  • Mathematical Modeling and Optimization

    Hart, William E. (et al.)

    Pages 15-27

  • Pyomo Overview

    Hart, William E. (et al.)

    Pages 29-45

  • Pyomo Models and Components: An Introduction

    Hart, William E. (et al.)

    Pages 47-77

  • The Pyomo Command

    Hart, William E. (et al.)

    Pages 79-96

Buy this book

eBook n/a
  • ISBN 978-3-319-58821-6
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-3-319-58819-3
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Pyomo — Optimization Modeling in Python
Authors
Series Title
Springer Optimization and Its Applications
Series Volume
67
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-58821-6
DOI
10.1007/978-3-319-58821-6
Hardcover ISBN
978-3-319-58819-3
Series ISSN
1931-6828
Edition Number
2
Number of Pages
XVIII, 277
Number of Illustrations and Tables
5 b/w illustrations, 8 illustrations in colour
Topics