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This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
1 Optimization Problem Formulation.- 1.1 Optimization Problem Formulation.- 1.2 The Standard Form of an Optimization Problem.- 1.3 Solution of Optimization Problems.- 1.4 Time Value of Money.- 1.5 Concluding Remarks.- 1.6 Problems.- 2 Graphical Optimization.- 2.1 Procedure for Graphical Optimization.- 2.2 GraphicalSolution function.- 2.3 Graphical Optimization Examples.- 2.4 Problems.- 3 Mathematical Preliminaries.- 3.1 Vectors and Matrices.- 3.2 Approximation Using the Taylor Series.- 3.3 Solution of Nonlinear Equations.- 3.4 Quadratic Forms.- 3.5 Convex Functions and Convex Optimization Problems.- 3.6 Problems.- 4 Optimality Conditions.- 4.1 Optimality Conditions for Unconstrained Problems.- 4.2 The Additive Property of Constraints.- 4.3 Karush-Kuhn-Tucker (KT) Conditions.- 4.4 Geometric Interpretation of KT Conditions.- 4.5 Sensitivity Analysis.- 4.6 Optimality Conditions for Convex Problems.- 4.7 Second-Order Sufficient Conditions.- 4.8 Lagrangian Duality.- 4.9 Problems.- 5 Unconstrained Problems.- 5.1 Descent direction.- 5.2 Line Search Techniques—Step Length Calculations.- 5.3 Unconstrained Minimization Techniques.- 5.4 Concluding Remarks.- 5.5 Problems.- 6 Linear Programming.- 6.1 The Standard LP Problem.- 6.2 Solving a Linear System of Equations.- 6.3 Basic Solutions of an LP Problem.- 6.4 The Simplex Method.- 6.5 Unusual Situations Arising During the Simplex Solution.- 6.6 Post-Optimality Analysis.- 6.7 The Revised Simplex Method.- 6.8 Sensitivity Analysis Using the Revised Simplex Method.- 6.9 Concluding Remarks.- 6.10 Problems.- 7 Interior Point Methods.- 7.1 Optimality Conditions for Standard LP.- 7.2 The Primal Affine Scaling Method.- 7.3 The Primal-Dual Interior Point Method.- 7.4 Concluding Remarks.- 7.5 Appendix—Null and Range Spaces.- 7.6 Problems.- 8 Quadratic Programming.- 8.1 KT Conditions for Standard QP.- 8.2 The Primal Affine Scaling Method for Convex QP.- 8.3 The Primal-Dual Method for Convex QP.- 8.4 Active Set Method.- 8.5 Active Set Method for the Dual QP Problem.- 8.6 Appendix—Derivation of the Descent Direction Formula for the PAS Method.- 8.7 Problems.- 9 Constrained Nonlinear Problems.- 9.1 Normalization.- 9.2 Penalty Methods.- 9.3 Linearization of a Nonlinear Problem.- 9.4 Sequential Linear Programming—SLP.- 9.5 Basic Sequential Quadratic Programming—SQP.- 9.6 Refined SQP Methods.- 9.7 Problems.- A.1 Basic Manipulations in Mathematica.- A.2 Lists and Matrices.- A.3 Solving Equations.- A.7 Online Help.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer Nature
- Data di pubblicazione2013
- ISBN 10 1461267919
- ISBN 13 9781461267911
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero di pagine732
- Contatto del produttorenon disponibile
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Practical Optimization Methods : With Mathematica® Applications
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are oft. Codice articolo 4189433
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This introductory textbook adopts a practical and intuitive approach, rather than emphasizing mathematical rigor. Computationally oriented books in this area generally present algorithms alone, and expect readers to perform computations by hand, and are often written in traditional computer languages, such as Basic, Fortran or Pascal. This book, on the other hand, is the first text to use Mathematica to develop a thorough understanding of optimization algorithms, fully exploiting Mathematica's symbolic, numerical and graphic capabilities. 732 pp. Englisch. Codice articolo 9781461267911
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Practical Optimization Methods
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Taschenbuch. Condizione: Neu. Neuware -The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some where in between these two extremes is adopted in this book. Theory is pre sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de veloped in an informal style by appealing to readers' intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v ' Preface VI -------------------------------------------------------- is presented.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 732 pp. Englisch. Codice articolo 9781461267911
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Practical Optimization Methods : With Mathematica® Applications
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Springer New York, Springer New York, 2013
ISBN 10: 1461267919
ISBN 13: 9781461267911
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The goal of this book is to present basic optimization theory and modern computational algorithms in a concise manner. The book is suitable for un dergraduate and graduate students in all branches of engineering, operations research, and management information systems. The book should also be use ful for practitioners who are interested in learning optimization and using these techniques on their own. Most available books in the field tend to be either too theoretical or present computational algorithms in a cookbook style. An approach that falls some where in between these two extremes is adopted in this book. Theory is pre sented in an informal style to make sense to most undergraduate and graduate students in engineering and business. Computational algorithms are also de veloped in an informal style by appealing to readers' intuition rather than mathematical rigor. The available, computationally oriented books generally present algorithms alone and expect readers to perform computations by hand or implement these algorithms by themselves. This obviously is unrealistic for a usual introductory optimization course in which a wide variety of optimization algorithms are discussed. There are some books that present programs written in traditional computer languages such as Basic, FORTRAN, or Pascal. These programs help with computations, but are of limited value in developing understanding of the algorithms because very little information about the intermediate steps v ' Preface VI -------------------------------------------------------- is presented. Codice articolo 9781461267911
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