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010 _a 2019744648
020 _a9783030689308 (pbk.)
024 7 _a10.1007/978-3-319-58821-6
_2doi
035 _a(DE-He213)978-3-319-58821-6
040 _aDLC
_beng
_epn
_erda
_cJKRC
072 7 _aMAT003000
_2bisacsh
072 7 _aPBU
_2bicssc
072 7 _aPBU
_2thema
082 0 4 _a519.6
_223
_bBYN.M
100 1 _aBynum, Michael L.
_eAuthor.
_931773
245 1 0 _aPyomo - optimization modeling in Python /
_cby Michael L. Bynum et. al...
_hEnglish.
250 _a3rd ed.
260 _aSwitzerland :
_bSpringer Nature,
_c2021.
300 _axvii, 225 p.
_c23 cm.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Optimization and Its Applications,
_x1931-6828 ;
_v67
505 0 _a1. 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.
520 _aThis 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. 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. Review of the first edition: Documents a simple, yet versatile tool for modeling and solving optimization problems... The book, by Bill Hart, Carl Laird, Jean-Paul Watson, and David Woodruff, is essential to the usability of Pyomo, serving as the Pyomo documentation... has contents for both an inexperienced user, and a computational operations research expert... with examples of each of the concepts discussed. -Nedialko B. Dimitrov, INFORMS Journal on Computing, Vol. 24 (4), Fall 2012.
588 _aDescription based on publisher-supplied MARC data.
650 0 _aComputer mathematics.
_92750
650 0 _aComputer science-Mathematics.
_931774
650 0 _aComputer simulation.
_931775
650 0 _aComputer software.
_919666
650 0 _aManagement science.
_931776
650 0 _aMathematical optimization.
_931777
650 0 _aOperations research.
_920234
650 1 4 _aOptimization.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M26008
_918712
650 2 4 _aComputational Mathematics and Numerical Analysis.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M1400X
_917920
650 2 4 _aMath Applications in Computer Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I17044
_931778
650 2 4 _aMathematical Software.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M14042
_931779
650 2 4 _aOperations Research, Management Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M26024
_931780
650 2 4 _aSimulation and Modeling.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I19000
_931781
700 1 _aHackebeil, Gabriel A.
_eAuthor.
_931782
700 1 _aHart, William E.
_eAuthor.
_931783
700 1 _aLaird, Carl D.
_eAuthor.
_931784
700 1 _aNicholson, Bethany L.
_eAuthor.
_931785
700 1 _aSiirola, John D.
_eAuthor.
_931786
700 1 _aWatson, Jean-Paul.
_eAuthor.
_931787
700 1 _aWoodruff, David L.
_eAuthor.
_931788
776 0 8 _iPrint version:
_tPyomo -- optimization modeling in Python
_z9783319588193
_w(DLC) 2017940404
776 0 8 _iPrinted edition:
_z9783319588193
776 0 8 _iPrinted edition:
_z9783319588209
776 0 8 _iPrinted edition:
_z9783319864822
830 0 _aSpringer Optimization and Its Applications,
_x1931-6828 ;
_v67
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