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Titlebook: Computational Combinatorial Optimization; Optimal or Provably Michael Jünger,Denis Naddef Textbook 2001 Springer-Verlag Berlin Heidelberg

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書目名稱Computational Combinatorial Optimization
副標(biāo)題Optimal or Provably
編輯Michael Jünger,Denis Naddef
視頻videohttp://file.papertrans.cn/233/232202/232202.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Combinatorial Optimization; Optimal or Provably  Michael Jünger,Denis Naddef Textbook 2001 Springer-Verlag Berlin Heidelberg
描述This tutorial contains written versions of seven lectures on Computational Combinatorial Optimization given by leading members of the optimization community. The lectures introduce modern combinatorial optimization techniques, with an emphasis on branch and cut algorithms and Lagrangian relaxation approaches. Polyhedral combinatorics as the mathematical backbone of successful algorithms are covered from many perspectives, in particular, polyhedral projection and lifting techniques and the importance of modeling are extensively discussed. Applications to prominent combinatorial optimization problems, e.g., in production and transport planning, are treated in many places; in particular, the book contains a state-of-the-art account of the most successful techniques for solving the traveling salesman problem to optimality.
出版日期Textbook 2001
關(guān)鍵詞Branch and Cut Algorithms; Combinatorial Optimization; Computational Combinatorial Optimization; Discre
版次1
doihttps://doi.org/10.1007/3-540-45586-8
isbn_softcover978-3-540-42877-0
isbn_ebook978-3-540-45586-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2001
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232202.jpg
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https://doi.org/10.1007/978-3-642-99292-6sections deal with those basic properties of projection that make it such an effiective and useful bridge between problem formulations in different spaces, i.e. different sets of variables. They discuss topics like the integrality-preserving property of projection, the dimension of projected polyhed
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https://doi.org/10.1007/978-3-642-99292-6tion planning problems. The objective is to present the classical optimization approaches used, and the known models, for dealing with such management problems..We describe first production planning models in the general context of manufacturing planning and control systems, and explain in which sen
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https://doi.org/10.1007/978-3-642-94618-9on problems to optimality (or, at least, with certified quality). In this unit, we concentrate on sequential branch-and-cut for hard combinatorial optimization problems, while branch-and-cut for general mixed integer linear programming is treated in [→ Martin] and parallel branch-and-cut is treated
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Manuel Krahwinkel,Rolf Kindmann used subtour inequalities as well as cutting planes of Gomory‘s type. The practice of looking for and using cuts that match prescribed templates in conjunction with Gomory cuts was continued in computer codes of Miliotis, Land, and Fleischmann. Gr?tschel, Padberg, and Hong advocated a different pol
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https://doi.org/10.1007/3-540-45586-8Branch and Cut Algorithms; Combinatorial Optimization; Computational Combinatorial Optimization; Discre
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