A simple, powerful method that is iterative and useful in a variety of settings for exact and approximate optimization.
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Lap-Chi Lau is an Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong. Lap-Chi's main research interests are in combinatorial optimization and graph algorithms. His paper on Steiner tree packing was given the Machtey award in the IEEE Foundations of Computer Science Conference. His Ph.D. thesis was awarded the Doctoral Prize from the Canadian Mathematical Society and a Doctoral Prize from the Natural Sciences and Engineering Research Council of Canada.
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Zustand: New. A simple, powerful method that is iterative and useful in a variety of settings for exact and approximate optimization. Series: Cambridge Texts in Applied Mathematics. Num Pages: 254 pages, 44 b/w illus. 102 exercises. BIC Classification: PBU; PBV; UMB. Category: (U) Tertiary Education (US: College). Dimension: 228 x 152 x 18. Weight in Grams: 480. . 2011. Illustrated. hardcover. . . . . Books ship from the US and Ireland. Artikel-Nr. V9781107007512
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - With the advent of approximation algorithms for NP-hard combinatorial optimization problems, several techniques from exact optimization such as the primal-dual method have proven their staying power and versatility. This book describes a simple and powerful method that is iterative in essence and similarly useful in a variety of settings for exact and approximate optimization. The authors highlight the commonality and uses of this method to prove a variety of classical polyhedral results on matchings, trees, matroids and flows. The presentation style is elementary enough to be accessible to anyone with exposure to basic linear algebra and graph theory, making the book suitable for introductory courses in combinatorial optimization at the upper undergraduate and beginning graduate levels. Discussions of advanced applications illustrate their potential for future application in research in approximation algorithms. Artikel-Nr. 9781107007512
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