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Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Published by Cambridge University Press, 2021
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ISBN 10: 1108831656 ISBN 13: 9781108831659
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Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Hardcover. Condition: new. Hardcover. Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering. A unique text covering basic and advanced concepts of optimization theory and methods for process systems engineers. With examples illustrating key concepts and algorithms, and exercises involving theoretical derivations, numerical problems and modeling systems, it is ideal for single-semester, graduate courses in process systems engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Hardback. Condition: New. Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Language: English
Published by Cambridge University Press Aug 2021, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
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Buch. Condition: Neu. Neuware - Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering.
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Hardcover. Condition: Brand New. 200 pages. 9.50x7.25x0.50 inches. In Stock.
Language: English
Published by Cambridge University Press, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
Seller: preigu, Osnabrück, Germany
Buch. Condition: Neu. Advanced Optimization for Process Systems Engineering | Ignacio E. Grossmann | Buch | Gebunden | Englisch | 2021 | Cambridge University Press | EAN 9781108831659 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Language: English
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831656 ISBN 13: 9781108831659
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. Based on the author's forty years of teaching experience, this unique textbook covers both basic and advanced concepts of optimization theory and methods for process systems engineers. Topics covered include continuous, discrete and logic optimization (linear, nonlinear, mixed-integer and generalized disjunctive programming), optimization under uncertainty (stochastic programming and flexibility analysis), and decomposition techniques (Lagrangean and Benders decomposition). Assuming only a basic background in calculus and linear algebra, it enables easy understanding of mathematical reasoning, and numerous examples throughout illustrate key concepts and algorithms. End-of-chapter exercises involving theoretical derivations and small numerical problems, as well as in modeling systems like GAMS, enhance understanding and help put knowledge into practice. Accompanied by two appendices containing web links to modeling systems and models related to applications in PSE, this is an essential text for single-semester, graduate courses in process systems engineering in departments of chemical engineering.