本站提供 8500 多本免费的 IT 技术电子书在线下载。
  1. 文章总数:8391
  2. 浏览总数:1,003,014
  3. 评论:0
  4. 分类目录:125 个
  5. 注册用户数:31
  6. 最后更新:2020年2月29日
过往记忆博客公共帐号iteblog_hadoop
欢迎关注微信公共帐号:
iteblog_hadoop

Linear and Nonlinear Programming, 4 edition

计算机科学 iteblog 141℃ 0评论

子标题:International Series in Operations Research & Management Science

Linear and Nonlinear Programming, 4 edition
作者:
David G. Luenberger, Yinyu Ye
ISBN-10:
3319188410
出版年份:
2015
页数:
546
语言:
English
文件大小:
5,49 MB
文件格式:
PDF

图书描述

This new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the fourth edition expands and further illustrates this relationship. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities.

New to this edition is a chapter devoted to Conic Linear Programming, a powerful generalization of Linear Programming. Indeed, many conic structures are possible and useful in a variety of applications. It must be recognized, however, that conic linear programming is an advanced topic, requiring special study. Another important topic is an accelerated steepest descent method that exhibits superior convergence properties, and for this reason, has become quite popular. The proof of the convergence property for both standard and accelerated steepest descent methods are presented in Chapter 8. As in previous editions, end-of-chapter exercises appear for all chapters.

点击进入下载

喜欢 (0)or分享 (0)
发表我的评论
取消评论

表情
本博客评论系统带有自动识别垃圾评论功能,请写一些有意义的评论,谢谢!