Pyomo — Optimization Modeling in Python

• Main Authors: Hart, William E. (Author), Laird, Carl D. (Author), Watson, Jean-Paul (Author), Woodruff, David L. (Author), Hackebeil, Gabriel A. (Author), Nicholson, Bethany L. (Author), Siirola, John D. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Edition: 2nd ed. 2017.
• Series: Springer Optimization and Its Applications, 67
• Subjects: Mathematics.; Computer science > Mathematics.; Computer simulation.; Computer mathematics.; Computer software.; Mathematical optimization.; Operations research.; Management science.; Optimization.; Simulation and Modeling.; Computational Mathematics and Numerical Analysis.; Math Applications in Computer Science.; Mathematical Software.; Operations Research, Management Science.

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...

Table of Contents:

• 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.