| Description |
1 online resource (231 pages) |
| Series |
Springer Optimization and Its Applications ; v. 67 |
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Springer optimization and its applications ; v. 67.
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| Contents |
Intro -- Preface -- Goals of the Book -- Who Should Read This Book -- Revisions for the Third Edition -- Acknowledgments -- Disclaimers -- Comments and Questions -- Contents -- Chapter 1 Introduction -- 1.1 Modeling Languages for Optimization -- 1.2 Modeling with Pyomo -- 1.2.1 Simple Examples -- 1.2.2 Graph Coloring Example -- 1.2.3 Key Pyomo Features -- Python -- Customizable Capability -- Command-Line Tools and Scripting -- Concrete and Abstract Model Definitions -- Object-Oriented Design -- Expressive Modeling Capability -- Solver Integration -- Open Source -- 1.3 Getting Started |
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1.4 Book Summary -- 1.5 Discussion -- Part I An Introduction to Pyomo -- Chapter 2 Mathematical Modeling and Optimization -- 2.1 Mathematical Modeling -- 2.1.1 Overview -- 2.1.2 A Modeling Example -- 2.2 Optimization -- 2.3 Modeling with Pyomo -- 2.3.1 A Concrete Formulation -- 2.4 Linear and Nonlinear Optimization Models -- 2.4.1 Definition -- 2.4.2 Linear Version -- 2.5 Solving the Pyomo Model -- 2.5.1 Solvers -- 2.5.2 Python Scripts -- Chapter 3 Pyomo Overview -- 3.1 Introduction -- 3.2 The Warehouse Location Problem -- 3.3 Pyomo Models |
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3.3.1 Components for Variables, Objectives, and Constraints -- 3.3.2 Indexed Components -- 3.3.3 Construction Rules -- 3.3.4 A Concrete Model for the Warehouse Location Problem -- 3.3.5 Modeling Components for Sets and Parameters -- Chapter 4 Pyomo Models and Components: An Introduction -- 4.1 An Object-Oriented AML -- 4.2 Common Component Paradigms -- 4.2.1 Indexed Components -- 4.3 Variables -- 4.3.1 Var Declarations -- 4.3.2 Working with Var Objects -- 4.4 Objectives -- 4.4.1 Objective Declarations -- 4.4.2 Working with Objective Objects -- 4.5 Constraints -- 4.5.1 Constraint Declarations |
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4.5.2 Working with Constraint Objects -- 4.6 Set Data -- 4.6.1 Set Declarations -- 4.6.2 Working with Set Objects -- 4.7 Parameter Data -- 4.7.1 Param Declarations -- 4.7.2 Working with Param Objects -- 4.8 Named Expressions -- 4.8.1 Expression Declarations -- 4.8.2 Working with Expression Objects -- 4.9 Suffix Components -- 4.9.1 Suffix Declarations -- 4.9.2 Working with Suffixes -- 4.10 Other Modeling Components -- Chapter 5 Scripting Custom Workflows -- 5.1 Introduction -- 5.2 Interrogating the Model -- 5.2.1 The The value Function -- 5.2.2 Accessing Attributes of Indexed Components |
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5.2.2.1 Slicing Over Indices of Components -- 5.2.2.2 Iterating Over All Var Objects on a Model -- 5.3 Modifying Pyomo Model Structure -- 5.4 Examples of Common Scripting Tasks -- 5.4.1 Warehouse Location Loop and Plotting -- 5.4.2 A Sudoku Solver -- Chapter 6 Interacting with Solvers -- 6.1 Introduction -- 6.2 Using Solvers -- 6.3 Investigating the Solution -- 6.3.1 Solver Results -- Part II Advanced Topics -- Chapter 7 Nonlinear Programming with Pyomo -- 7.1 Introduction -- 7.2 Nonlinear Progamming Problems in Pyomo -- 7.2.1 Nonlinear Expressions -- 7.2.2 The Rosenbrock Problem |
| Summary |
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. In the third edition, much of the material has been reorganized, new examples have been added, and a new chapter has been added describing how modelers can improve the performance of their models. The authors have also modified their recommended method for importing Pyomo. A big change in this edition is the emphasis of concrete models, which provide fewer restrictions on the specification and use of Pyomo models. 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. Review of the Second edition: 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 |
| Notes |
7.3 Solving Nonlinear Programming Formulations |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Computer simulation.
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Mathematical optimization -- Computer simulation
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Python (Computer program language)
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Computer Simulation
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simulation.
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Optimización matemática -- Simulación por ordenador
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Python (Lenguaje de programación)
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Computer simulation
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Python (Computer program language)
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Simulació per ordinador.
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Optimització matemàtica.
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Python (Llenguatge de programació)
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| Genre/Form |
Llibres electrònics.
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| Form |
Electronic book
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| Author |
Hackebeil, Gabriel A
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Hart, William E
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Laird, Carl D
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Nicholson, Bethany L
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Siirola, John D. (John Daniel)
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Watson, Jean-Paul
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Woodruff, David L
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| ISBN |
9783030689285 |
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303068928X |
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9783030689292 |
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3030689298 |
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9783030689308 |
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3030689301 |
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