About this product

Product Identifiers

PublisherSpringer International Publishing A&G

ISBN-103030689301

ISBN-139783030689308

eBay Product ID (ePID)15057275922

Product Key Features

Number of PagesXvii, 225 Pages

Publication NamePyomo -- Optimization Modeling in Python

LanguageEnglish

Publication Year2022

SubjectComputer Simulation, Numerical Analysis, General, Optimization

TypeTextbook

Subject AreaMathematics, Computers

AuthorGabriel A. Hackebeil, Michael L. Bynum, William E. Hart, Carl D. Laird, Bethany L. Nicholson

SeriesSpringer Optimization and Its Applications Ser.

FormatTrade Paperback

Dimensions

Item Weight13.4 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Edition Number3

Dewey Edition23

Series Volume Number67

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal519.6

Table Of Content1. Introduction.- Part I. An Introduction to Pyomo.- 2. Mathematical Modeling and Optimization.- 3. Pyomo Overview.- 4. Pyomo Models and Components: An Introduction.- 5. Scripting Custom Workflows.- 6. Interacting with Solvers.- Part II. Advanced Topics.- 7. Nonlinear Programming with Pyomo.- 8. Structured Modeling with Blocks.- 9. Performance: Model Construction and Solver Interfaces.- 10. Abstract Models and Their Solution.- Part III. Modeling Extensions.- 11. Generalized Disjunctive Programming.- 12. Differential Algebraic Equations.- 13. Mathematical Programs with Equilibrium Constraints.- . A Brief Python Tutorial.- Bibliography.- Index.

SynopsisThis 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.

LC Classification NumberQA402.5-402.6