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Pyomo — Optimization Modeling in Python Vital Source e-bog
William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
(2017)
Pyomo — Optimization Modeling in Python Vital Source e-bog
William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
(2017)
Pyomo — Optimization Modeling in Python Vital Source e-bog
William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
(2017)
Pyomo -- Optimization Modeling in Python
William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany L. Nicholson og John D. Siirola
(2017)
Sprog: Engelsk
Detaljer om varen
- 2. Udgave
- Vital Source searchable e-book (Fixed pages)
- Udgiver: Springer Nature (Maj 2017)
- Forfattere: William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
- ISBN: 9783319588216
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Detaljer om varen
- 2. Udgave
- Vital Source 90 day rentals (fixed pages)
- Udgiver: Springer Nature (Maj 2017)
- Forfattere: William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
- ISBN: 9783319588216R90
Bookshelf online: 90 dage fra købsdato.
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Detaljer om varen
- 2. Udgave
- Vital Source 180 day rentals (fixed pages)
- Udgiver: Springer Nature (Maj 2017)
- Forfattere: William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil og Bethany L
- ISBN: 9783319588216R180
Bookshelf online: 180 dage fra købsdato.
Bookshelf appen: 180 dage fra købsdato.
Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
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Detaljer om varen
- Hardback
- Udgiver: Springer International Publishing AG (Juni 2017)
- Forfattere: William E. Hart, Carl D. Laird, Jean-Paul Watson, David L. Woodruff, Gabriel A. Hackebeil, Bethany L. Nicholson og John D. Siirola
- ISBN: 9783319588193
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.
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.