Hardcover. The first edition of Integrated Methods for Optimization was published in January 2007. Because the book covers a rapidly developing field, the time is right for a second edition. The book provides a unified treatment of optimization methods. It brings ideas from mathematical programming (MP), constraint programming (CP), and global optimization (GO)into a single volume. There is no reason these must be learned as separate fields, as they normally are, and there are three reasons they should be studied together. (1) There is much in common among them intellectually, and to a large degree they can be understood as special cases of a single underlying solution technology. (2) A growing literature reports how they can be profitably integrated to formulate and solve a wide range of problems. (3) Several software packages now incorporate techniques from two or more of these fields.The book provides a unique resource for graduate students and practitioners who want a well-rounded background in optimization methods within a single course of study. Engineering students are a particularly large potential audience, because engineering optimization problems often benefit from a combined approachparticularly where design, scheduling, or logistics are involved. The text is also of value to those studying operations research, because their educational programs rarely cover CP, and to those studying computer science and artificial intelligence (AI), because their curricula typically omit MP and GO. The text is also useful for practitioners in any of these areas who want to learn about another, because it provides a more concise and accessible treatment than other texts.The book can cover so wide a range of material because it focuses on ideas that arerelevant to the methods used in general-purpose optimization and constraint solvers. The book focuses on ideas behind the methods that have proved useful in general-purpose optimization and constraint solvers, as well as integrated solvers of the present and foreseeable future. The second edition updates results in this area and includes several major new topics:Background material in linear, nonlinear, and dynamic programming.Network flow theory, due to its importance in filtering algorithms.A chapter on generalized duality theory that more explicitly develops a unifying primal-dual algorithmic structure for optimization methods.An extensive survey of search methods from both MP and AI, using the primal-dual framework as an organizing principle.Coverage of several additional global constraints used in CP solvers.The book continues to focus on exact as opposed to heuristic methods. It is possible to bring heuristic methods into the unifying scheme described in the book, and the new edition will retain the brief discussion of how this might be done. Now in a fully updated second edition, with new chapters covering flow theory, state-of-the-art search methods and GO/nonlinear programming, this unified treatment of optimization methods deals with all facets of the topic needed by students and practitioners. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Integrated Methods for Optimization (Hardcover)
Editor: Springer-Verlag New York Inc., New York, NY
Fecha de publicaci�n: 2011
Idioma: Ingl�s
ISBN 10: 1461418992
ISBN 13: 9781461418993
Encuadernaci�n: Hardcover
Edici�n: 2� Edici�n
Estado: new

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Sinopsis

The first edition of Integrated Methods for Optimization was published in January 2007. Because the book covers a rapidly developing field, the time is right for a second edition. The book provides a unified treatment of optimization methods. It brings ideas from mathematical programming (MP), constraint programming (CP), and global optimization (GO)into a single volume. There is no reason these must be learned as separate fields, as they normally are, and there are three reasons they should be studied together. (1) There is much in common among them intellectually, and to a large degree they can be understood as special cases of a single underlying solution technology. (2) A growing literature reports how they can be profitably integrated to formulate and solve a wide range of problems. (3) Several software packages now incorporate techniques from two or more of these fields.

The book provides a unique resource for graduate students and practitioners who want a well-rounded background in optimization methods within a single course of study. Engineering students are a particularly large potential audience, because engineering optimization problems often benefit from a combined approach-particularly where design, scheduling, or logistics are involved. The text is also of value to those studying operations research, because their educational programs rarely cover CP, and to those studying computer science and artificial intelligence (AI), because their curric

ula typically omit MP and GO. The text is also useful for practitioners in any of these areas who want to learn about another, because it provides a more concise and accessible treatment than other texts.

The book can cover so wide a range of material because it focuses on ideas that arerelevant to the methods used in general-purpose optimization and constraint solvers. The book focuses on ideas behind the methods that have proved useful in general-purpose optimization and constraint solvers, as well as integrated solvers of the present and foreseeable future. The second edition updates results in this area and includes several major new topics:

Background material in linear, nonlinear, and dynamic programming.
Network flow theory, due to its importance in filtering algorithms.
A chapter on generalized duality theory that more explicitly develops a unifying primal-dual algorithmic structure for optimization methods.
An extensive survey of search methods from both MP and AI, using the primal-dual framework as an organizing principle.
Coverage of several additional global constraints used in CP solvers.

The book continues to focus on exact as opposed to heuristic methods. It is possible to bring heuristic methods into the unifying scheme described in the book, and the new edition will retain the brief discussion of how this might be done.

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John Hooker is T. Jerome Holleran Professor of Business Ethics and Social Responsibility, and Professor of Operations Research, at Carnegie Mellon University. He is also part-time Visiting Professor at London School of Economics, 2009-2011. He holds doctoral degrees in philosophy and management science. His research interests include operations research, business ethics, and cross-cultural issues. He teaches courses in these fields at the undergraduate, postgraduate, and executive levels, and he has published over 130 articles and seven books. He is founding editor-in-chief of the Journal of Business Ethics Education and an area editor for INFORMS Journal on Computing. He is founding director of the Center for International Corporate Responsibility at Carnegie Mellon. He was recently named an INFORMS Fellow for outstanding contributions to operations research and the management sciences. His recent book Integrated Methods for Optimization reflects his primary research interests in operations research. He developed the ethics curriculum, including course materials, used in CMU's Tepper School of Business, and he has co-organized four conferences on international corporate responsibility. His book Working across Cultures is used as a text in cross-cultural business courses at several universities. He has lived and worked in Australia, China, Denmark, India, Qatar, Turkey, the United States, and Zimbabwe, and has extensive experience in Germany, Mexico, and the United Kingdom. He has led professional workshops in several countries. He was head of Carnegie Mellon's undergraduate Business Administration Program 1996-2001. He reorganized the program, led the design of its curriculum, and received a distinguished service award from the Tepper School for his contributions. In 2009 he received an Award for Sustained Teaching Excellence in the program.

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