Published by Springer, 2004
Language: English
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Add to basketHardcover. Condition: Wie neu. 402 S., Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 980.
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Published by Kluwer Academic Publishers, 1998
ISBN 10: 0792350189 ISBN 13: 9780792350187
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Published by Kluwer Academic Publishers, 1998
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air line crew scheduling, corporate planning, computer-aided design and man ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, alloca tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In addi tion, linear programming relaxations are often the basis for many approxi mation algorithms for solving NP-hard problems (e.g. dualheuristics).
Published by Springer US, Springer US, 1999
ISBN 10: 0792359240 ISBN 13: 9780792359241
Language: English
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied math ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, air line crew scheduling, corporate planning, computer-aided design and man ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, alloca tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discover ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These algo rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In addi tion, linear programming relaxations are often the basis for many approxi mation algorithms for solving NP-hard problems (e.g. dualheuristics).
Published by Springer, 2005
Language: English
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Published by Springer-Verlag New York Inc., New York, NY, 2011
ISBN 10: 1441936661 ISBN 13: 9781441936660
Language: English
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First Edition
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Add to basketPaperback. Condition: new. Paperback. Combinatorial (or discrete) optimization is one of the most active fields in the interface of operations research, computer science, and applied ma- ematics. Combinatorial optimization problems arise in various applications, including communications network design, VLSI design, machine vision, a- line crew scheduling, corporate planning, computer-aided design and m- ufacturing, database query design, cellular telephone frequency assignment, constraint directed reasoning, and computational biology. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. All these problems, when formulated mathematically as the minimization or maximization of a certain function defined on some domain, have a commonality of discreteness. Historically, combinatorial optimization starts with linear programming. Linear programming has an entire range of important applications including production planning and distribution, personnel assignment, finance, allo- tion of economic resources, circuit simulation, and control systems. Leonid Kantorovich and Tjalling Koopmans received the Nobel Prize (1975) for their work on the optimal allocation of resources. Two important discov- ies, the ellipsoid method (1979) and interior point approaches (1984) both provide polynomial time algorithms for linear programming. These al- rithms have had a profound effect in combinatorial optimization. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. matching and maximum flow). In ad- tion, linear programming relaxations are often the basis for many appro- mation algorithms for solving NP-hard problems (e.g. dual heuristics). Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Kluwer Academic Publishers, Dordrecht, 1999
ISBN 10: 0792359240 ISBN 13: 9780792359241
Language: English
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Add to basketHardcover. Condition: new. Hardcover. This volume can be considered as a supplementary volume to the three-volume "Handbook of Combinatorial Optimization" published by Kluwer. It can also be regarded as a stand-alone volume which presents chapters dealing with various aspects of the subject including optimization problems and algorithmic approaches for discrete problems. This handbook deals with several algorithmic approaches for discrete problems as well as with many combinatorial optimization problems. Each chapter in the handbook is expository in nature, but scholarly in treatment. The book is addressed not only to researchers in discrete optimization, but to all scientists in various disciplines who use combinatorial optimization methods to model and solve problems. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketCondition: New. The material presented in this supplement to the 3-volume Handbook of Combinatorial Optimization will be useful for any researcher who uses combinatorial optimization methods to solve problemsThe material presented in this supplement to the 3-volume .
Published by Springer-Verlag New York Inc., 2004
ISBN 10: 0387238298 ISBN 13: 9780387238296
Language: English
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Add to basketCondition: New. Presents chapters dealing with various aspects of the subject, including optimization problems and algorithmic approaches for discrete problems. This is a supplementary volume to the major three-volume "Handbook of Combinatorial Optimization" set, as well as the "Supplement Volume A". Num Pages: 402 pages, biography. BIC Classification: PBUH; PBV; PBW; UY. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 23. Weight in Grams: 742. . 2004. 2005th Edition. hardcover. . . . .
Published by Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10: 1441948139 ISBN 13: 9781441948137
Language: English
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First Edition
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Add to basketPaperback. Condition: new. Paperback. This volume can be considered as a supplementary volume to the major three-volume Handbook of Combinatorial Optimization published by Kluwer. It can also be regarded as a stand-alone volume which presents chapters dealing with various aspects of the subject including optimization problems and algorithmic approaches for discrete problems. Audience: All those who use combinatorial optimization methods to model and solve problems. Furthermore, combinatorial optimization problems occur in many diverse areas such as linear and integer programming, graph theory, artificial intelligence, and number theory. Many polynomial-time solvable combinatorial optimization problems are special cases of linear programming (e.g. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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