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Titlebook: Linear Programming Computation; Ping-Qi PAN Book 2023Latest edition The Editor(s) (if applicable) and The Author(s), under exclusive licen

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樓主
發(fā)表于 2025-3-21 17:00:10 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Linear Programming Computation
編輯Ping-Qi PAN
視頻videohttp://file.papertrans.cn/587/586395/586395.mp4
概述A landmark work on LP.An updated edition with important improvements.A must-read for students, researchers, and practitioners interested in LP and related areas
圖書封面Titlebook: Linear Programming Computation;  Ping-Qi PAN Book 2023Latest edition The Editor(s) (if applicable) and The Author(s), under exclusive licen
描述.This monograph represents a historic breakthrough in the field of linear programming (LP)since George Dantzig first discovered the simplex method in 1947...Being both thoughtful and informative, it focuses on reflecting and promoting the state of the art by highlighting new achievements in LP. This new edition is organized in two volumes. The first volume addresses foundations of LP, including the geometry of feasible region, the simplex method and its implementation, duality and the dual simplex method, the primal-dual simplex method, sensitivity analysis and parametric LP, the generalized simplex method, the decomposition method, the interior-point method and integer LP method. The second volume mainly introduces contributions of the author himself, such as efficient primal/dual pivot rules, primal/dual Phase-I methods, reduced/D-reduced simplex methods, the generalized reduced simplex method, primal/dual deficient-basis methods, primal/dual face methods, a new decomposition principle, etc..Many important improvements were made in this edition. The first volume includes new results, such as the mixed two-phase simplex algorithm, dual elimination, fresh pricing scheme for reduced
出版日期Book 2023Latest edition
關(guān)鍵詞deficient-basis method; duality and dual simplex method; face method; linear programming; reduced simple
版次2
doihttps://doi.org/10.1007/978-981-19-0147-8
isbn_softcover978-981-19-0149-2
isbn_ebook978-981-19-0147-8
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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沙發(fā)
發(fā)表于 2025-3-21 20:19:37 | 只看該作者
978-981-19-0149-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Implementation of Simplex MethodAll algorithms formulated in this book, such as the simplex algorithm and the dual simplex algorithm, are theoretical or conceptual and cannot be put into use directly. Software, resulting by the following algorithms, step by step would solve textbook instances only. Implementation techniques are crucial to the success of optimization methods.
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Decomposition MethodSolving large-scale LP problems is a challenging task, putting forward high requirements on the algorithms’ efficiency, storage, and numerical stability. The decomposition method divides a large-scale LP problem into relatively small ones to cope with normal LP solvers.
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發(fā)表于 2025-3-22 19:27:50 | 只看該作者
Interior-Point MethodAs it is known, the simplex method moves on the underlying polyhedron, from vertex to adjacent vertex along edges, until attaining an optimal vertex unless the lower unboundedness is detected. Nevertheless, it could go through an exponential number of vertices of the polyhedron and even stay at a vertex forever because of cycling (Sect. .).
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