Pyomo optimization modeling in Python
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. Modeling is a fundamental process in many aspects of scient...
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| Hlavní autoři: | , , , |
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| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2012. |
| Edice: | Springer Optimization and Its Applications
67 |
| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Autres contributeurs : Woodruff, David L. (auteur) Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Variante du titre: | Pyomo optimization modeling in Python |
| Edition sous un autre format: | • Pyomo Optimization Modeling in Python, Texte imprimé, 9781461432258 • Pyomo - Optimization Modeling in Python, Texte imprimé, 9781461432272 • Pyomo - Optimization Modeling in Python, Texte imprimé, 9781489993250 |
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| 100 | 1 | |a Hart, William E., |d 19..- | |
| 240 | 1 | 0 | |a Pyomo optimization modeling in Python |
| 245 | 1 | 0 | |a Pyomo optimization modeling in Python |c William E. Hart, Carl Laird, Jean-Paul Watson, ... [et al.]. |
| 250 | |a 1st ed. 2012. | ||
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Springer Optimization and Its Applications |v 67 |x 1931-6836 | |
| 500 | |a Autres contributeurs : Woodruff, David L. (auteur) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Preface 1. Introduction 2. Pyomo Modeling Strategies 3. Model Components: Variables, Objectives and Constraints 4. Model Components: Sets and Parameters 5. Mischellaneous Model Components and Utility Functions 6. Initializing Abstract Models with Data Command Files 7. The Pyomo Command-Line Interface 8. Nonlinear Programming with Pyomo 9. Stochastic Programming Extensions 10. Scripting and Algorithm Development A. Installing Coopr B. A Brief Python Tutorial C. Pyomo and Coopr: The Bigger Picture Index | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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. Modeling is a fundamental process in many aspects of scientific research, engineering, and business. This text beautifully illustrates the breadth of the modeling capabilities that are supported by this new software and its handling of complex real-world applications. 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. The text begins with a tutorial on simple linear and integer programming models. Information needed to install and get started with the software is also provided. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from sources like spreadsheets and databases. The final chapters cover advanced topics such as nonlinear models, stochastic models, and scripting examples | ||
| 650 | |a Python (langage de programmation) | ||
| 650 | |a Optimisation mathématique | ||
| 700 | 1 | |a Laird, Carl D., |d 19..- |4 aut | |
| 700 | 1 | |a Watson, Jean-Paul, |d 19..- |4 aut | |
| 700 | 1 | |a Woodruff, David L., |d 19..- |4 aut | |
| 776 | 0 | |t Pyomo Optimization Modeling in Python |b Texte imprimé |z 9781461432258 | |
| 776 | 0 | |t Pyomo - Optimization Modeling in Python |b Texte imprimé |z 9781461432272 | |
| 776 | 0 | |t Pyomo - Optimization Modeling in Python |b Texte imprimé |z 9781489993250 | |
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