Overview
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 67)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (14 chapters)
-
Front Matter
-
An Introduction to Pyomo
-
Front Matter
-
-
Back Matter
Keywords
About this book
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.
Pyomois 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.
Reviews
Authors and Affiliations
About the authors
Bibliographic Information
Book Title: Pyomo — Optimization Modeling in Python
Authors: William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany L. Nicholson, John D. Siirola
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-319-58821-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-86482-2Published: 04 August 2018
eBook ISBN: 978-3-319-58821-6Published: 26 May 2017
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 2
Number of Pages: XVIII, 277
Number of Illustrations: 5 b/w illustrations, 8 illustrations in colour
Topics: Optimization, Simulation and Modeling, Computational Mathematics and Numerical Analysis, Math Applications in Computer Science, Mathematical Software, Operations Research, Management Science