Pyomo -- optimization modeling in Python

Pyomo -- optimization modeling in Python

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Bibliographic Details
Main Author: Bynum, Michael L.
Other Authors: Hackebeil, Gabriel A., Hart, William E., Laird, Carl D., Nicholson, Bethany L., Siirola, John D., Watson, Jean-Paul., Woodruff, David L.
Language:English
Edition:3rd ed.
Series:Springer optimization and its applications ; v. 67.
Subjects:
Computer simulation.
Mathematical optimization > Computer simulation.
Python (Computer program language)
Online Access:Link to e-book
Item Description:Description based upon print version of record.
7.3 Solving Nonlinear Programming Formulations.
Physical Description:1 online resource (231 p.).
Bibliography:Includes bibliographical references and index.
Published: Cham : Springer, 2021.
ISBN:9783030689285
303068928X
9783030689292
3030689298
9783030689308
3030689301
Table of 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
  • 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
  • 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
  • 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
  • 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

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