Pyomo — Optimization Modeling in Python
Springer International Publishing (Verlag)
978-3-319-58819-3 (ISBN)
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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.
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.
1. Introduction.- Part I. An Introduction to Pyomo.- 2. Mathematical Modeling and Optimization.- 3. Pyomo Overview.- 4. Pyomo Models and Components.- 5. The Pyomo Command.- 6. Data Command Files.- Part II. Advanced Features and Extensions.- 7. Nonlinear Programming with Pyomo.- 8. Structured Modeling with Blocks.- 9. Generalized Disjunctive Programming.- 10. Stochastic Programming Extensions.- 11. Differential Algebraic Equations.- 12. Mathematical Programs with Equilibrium Constraints.- 13. Bilevel Programming.- 14. Scripting.- A. A Brief Python Tutorial.- Index.
"This book provides a detailed guide to Pyomo for beginners and advanced users from undergraduate students to academic researchers to practitioners. ... the book is a good software guide which I strongly recommend to anybody interested in looking for an alternative to commercial modeling languages in general or in learning or intensifying their Pyomo skills in particular." (Christina Schenk, SIAM Review, Vol. 61 (1), March, 2019)
| Erscheinungsdatum | 23.06.2017 |
|---|---|
| Reihe/Serie | Springer Optimization and Its Applications ; 67 |
| Zusatzinfo | XVIII, 277 p. 13 illus., 8 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 631 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Schlagworte | 3D graphics & modelling • 3D graphics & modelling • algebraic modeling languages • Computational Mathematics and Numerical Analysis • Hybrid Optimization • management & management techniques • Management & management techniques • Math applications in computer science • Mathematical & statistical software • mathematical modeling tool • mathematical software • Mathematical & statistical software • Mathematics • mathematics and statistics • Maths for computer scientists • matplotlib • Modeling and Simulation • Numerical analysis • NumPy • Operational Research • Operations Research, Management Science • Optimization • Pyomo modeling library • Pyomo tutorial • PySP • Python data • Python optimization • Python script • SciPy • Simulation and modeling |
| ISBN-10 | 3-319-58819-2 / 3319588192 |
| ISBN-13 | 978-3-319-58819-3 / 9783319588193 |
| Zustand | Neuware |
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