Publicado por Springer, 2004
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Añadir al carritoHardcover. Condición: Wie neu. 402 S., Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 980.
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Añadir al carritoCondición: Good. 402 pp., Hardcover, ex library, light age toning to edges, else text and binding clean and tight. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: 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).
Publicado por Springer US, Springer US, 1999
ISBN 10: 0792359240 ISBN 13: 9780792359241
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 170,64
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Añadir al carritoBuch. Condición: 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).
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Añadir al carritoCondición: 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 .
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. supplement edition. 408 pages. 9.61x6.61x1.97 inches. In Stock.
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Añadir al carritoPaperback. Condición: Brand New. supplement edition. 656 pages. 9.25x6.25x1.49 inches. In Stock.
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Añadir al carritoPaperback. Condición: Like New. Like New. book.