MARC details
000 -LEADER |
fixed length control field |
02686nam a22002657a 4500 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240206175356.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
240206b |||||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783030689308 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
003.3 |
Item number |
BYN |
245 ## - TITLE STATEMENT |
Title |
Pyomo-optimization modeling in Python |
250 ## - EDITION STATEMENT |
Edition statement |
3rd ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Name of publisher, distributor, etc. |
Springer |
Place of publication, distribution, etc. |
Cham |
Date of publication, distribution, etc. |
2021 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xvii, 225 p. |
365 ## - TRADE PRICE |
Price type code |
EURO |
Price amount |
49.99 |
490 ## - SERIES STATEMENT |
Series statement |
Springer Optimization and Its Applications (SOIA, volume 67 ) |
520 ## - SUMMARY, ETC. |
Summary, etc. |
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 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. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming.<br/><br/>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.<br/><br/>(https://link.springer.com/book/10.1007/978-3-319-58821-6#about-this-book) |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Computer simulation |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Python (Computer program language) |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Mathematical optimization |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Computer software |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Bynum, Michael |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Laird, Carl D. |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Watson, Jean-Paul |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Book |
Source of classification or shelving scheme |
Dewey Decimal Classification |