Linear Programming Computation Softcover reprint of the original 1st ed. 2014 Edition

Linear Programming Computation Softcover reprint of the original 1st ed. 2014 Edition book cover

Linear Programming Computation Softcover reprint of the original 1st ed. 2014 Edition

Author(s): Ping-Qi PAN (Author)

  • Publisher: Springer
  • Publication Date: 3 Sept. 2016
  • Edition: Softcover reprint of the original 1st ed. 2014
  • Language: English
  • Print length: 768 pages
  • ISBN-10: 3662514303
  • ISBN-13: 9783662514306

Book Description

With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced results, including efficient pivot rules, Phase-I approaches, reduced simplex methods, deficient-basis methods, face methods, and pivotal interior-point methods. In particular, it covers the determination of the optimal solution set, feasible-point simplex method, decomposition principle for solving large-scale problems, controlled-branch method based on generalized reduced simplex framework for solving integer LP problems.

Editorial Reviews

Review

“Evidenced by superior performance in computational experiments, the author’s work has refreshed the state of the art of LP, and by its originality, breadth and depth, is having a major impact on the field of mathematical optimization.” (EJOR, European Journal of Operational Research, Vol. 267 (3), June, 2018)

“The book seems to be mainly addressed to scientists who already possess some expertise in LP. The kind of presentation, however, also allows using parts of it as a basis for a course on the topic. In fact, a special feature of the book is that an algorithm typically is accompanied by some example for which the results of all computational steps needed to find a solution are written down.” (Rembert Reemtsen, zbMATH, Vol. 1302, 2015)

“This book is a research monograph focusing on computational techniques in the simplex method for linear programming. … It may be of interest to researchers and developers of simplex method codes for linear programming.” (B. Borchers, Choice, Vol. 52 (3), November, 2014)

From the Back Cover

With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced results, including efficient pivot rules, Phase-I approaches, reduced simplex methods, deficient-basis methods, face methods, and pivotal interior-point methods. In particular, it covers the determination of the optimal solution set, feasible-point simplex method, decomposition principle for solving large-scale problems, controlled-branch method based on generalized reduced simplex framework for solving integer LP problems.

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