Pyomo – Optimization Modeling in Python - Info and Reading Options
By William E. Hart, Carl Laird, Jean-Paul Watson and David L. Woodruff
"Pyomo – Optimization Modeling in Python" was published by Springer New York in 2014, the book is classified in Mathematics genre, it has 238 pages and the language of the book is English.
“Pyomo – Optimization Modeling in Python” Metadata:
- Title: ➤ Pyomo – Optimization Modeling in Python
- Authors: William E. HartCarl LairdJean-Paul WatsonDavid L. Woodruff
- Language: English
- Number of Pages: 238
- Is Family Friendly: Yes - No Mature Content
- Publisher: Springer New York
- Publish Date: 2014
- Genres: Mathematics
Edition Specifications:
- Weight: 0.397
- Pagination: xviii, 238
Edition Identifiers:
- Google Books ID: fzr6oAEACAAJ
- The Open Library ID: OL37187863M - OL20896359W
- ISBN-13: 9781489993250
- ISBN-10: 1489993258
- All ISBNs: 9781489993250 - 1489993258
AI-generated Review of “Pyomo – Optimization Modeling in Python”:
Snippets and Summary:
This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and ...
"Pyomo – Optimization Modeling in Python" Description:
Google Books:
This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful 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 software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs.
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