现货 近似算法的设计 The Design of Approximation Algorithms PDF下载 公众号 其他格式

现货 近似算法的设计 The Design of Approximation Algorithms

进口原版 Computers & Internet(计算机与网络)

  • ISBN:9780521195270
  • 作者:David P Williamson & D...
  • 包装:简装
  • 版次:1
  • 页数:518
  • 出版社:Cambridge University P...
  • 外文名:CBG The Design of Appr...
  • 出版时间:2011-04-26
  • 正文语言:英语

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近似算法的设计 The Design of Approximation Algorithms
作者: David P. Williamson;David B. Shmoys
ISBN13: 9780521195270
类型: 简装(简装书)
语种: 英语(English)
出版日期: 2011-04-26
出版社: Cambridge University Press
页数: 518
重量(克): 1115
尺寸: 26.2382 x 18.923 x 3.4036 cm

商品简介
Designed as a textbook for graduate courses on algorithms, this book will also serve as a reference for researchers interested in heuristic solutions of discrete optimization problems. It presents central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization.
书评与摘要
Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing. Yet most such problems are NP-hard. Thus unless P = NP, there are no efficient algorithms to find optimal solutions to such problems. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first part of the book is devoted to a single algorithmic technique, which is then applied to several different problems. The second part revisits the techniques but offers more sophisticated treatments of them. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.

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