Mixed Integer Nonlinear Programming (The IMA Volumes in Mathematics and its Applications, 154)
ISBN 10: 1461419263 ISBN 13: 9781461419266
Editore: Springer, 2011
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<p>Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.</p>
Dalla quarta di copertina: ?Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.
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Titolo: Mixed Integer Nonlinear Programming (The IMA...
Casa editrice: Springer
Data di pubblicazione: 2011
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Mixed Integer Nonlinear Programming (The IMA Volumes in Mathematics and its Applications, 154)
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Hardcover. Condizione: Very Good+. Very good+ hardcover copy, from a personal collection (NOT ex-library). Binding is tight, sturdy, and square; boards and text also very good+. Exterior looks great. Pictorial boards, no dust jacket issued. May be a print-on-demand edition but of good quality. Ships from Dinkytown in Minneapolis, Minnesota. Due to the size/weight of this book extra charges may apply for international shipping. Codice articolo 294981
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Mixed Integer Nonlinear Programming (eng)
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Buch. Condizione: Neu. Mixed Integer Nonlinear Programming | Sven Leyffer (u. a.) | Buch | xx | Englisch | 2011 | Springer US | EAN 9781461419266 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Codice articolo 106780755
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Mixed Integer Nonlinear Programming
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Springer New York, Chapman And Hall/CRC Dez 2011, 2011
ISBN 10: 1461419263
ISBN 13: 9781461419266
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners - including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers - are interested in solving large-scale MINLP instances. 712 pp. Englisch. Codice articolo 9781461419266
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Mixed Integer Nonlinear Programming
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Springer New York, Springer New York Dez 2011, 2011
ISBN 10: 1461419263
ISBN 13: 9781461419266
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Buch. Condizione: Neu. Neuware -Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners ¿ including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers ¿ are interested in solving large-scale MINLP instances.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 712 pp. Englisch. Codice articolo 9781461419266
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Mixed Integer Nonlinear Programming
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ISBN 10: 1461419263
ISBN 13: 9781461419266
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners - including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers - are interested in solving large-scale MINLP instances. Codice articolo 9781461419266
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