Pyomo — Optimization Modeling in Python

Auteurs

• William E. Hart

Paramètres

• Mathématiques

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This book serves as a comprehensive guide to Pyomo (Python Optimization Modeling Objects) for both novice and experienced modelers, including undergraduate and graduate students, researchers, and practitioners. Through numerous examples, it illustrates various techniques for model formulation, showcasing Pyomo's extensive modeling capabilities and its application to complex real-world problems. The second edition expands on Pyomo’s features, offering a more detailed overview that empowers users to develop and optimize models effectively. Introductory chapters have been updated to enhance tutorials, while advanced chapters now incorporate new functionalities since the first edition, such as generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming. As an open-source software package, Pyomo is designed for formulating and solving large-scale optimization problems, extending the modeling approaches of modern Algebraic Modeling Language (AML) tools. It is a flexible, extensible, and portable AML embedded in Python, a dynamic programming language known for its clear syntax and intuitive object orientation. Pyomo provides Python classes for defining sparse sets, parameters, and variables, facilitating the formulation of algebraic expressions for objectives and constraints. Additionally, it can be utilized from a command-line interface or within Python's interactive environmen

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• Année de publication: 2018