Linear and Nonlinear Programming Fifth Edition (Hardcover)
暫譯: 線性與非線性規劃 第五版 (精裝本)

Luenberger, David G., Ye, Yinyu

Linear and Nonlinear Programming Fifth Edition (Hardcover)

商品描述

The 5th edition of this classic textbook 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 that problem. End-of-chapter exercises are provided for all chapters.

The material is organized into three separate parts. Part I offers 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. In turn, 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. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities.

 

New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas' lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.

 

商品描述(中文翻譯)

第五版的這本經典教科書涵蓋了實用優化技術的核心概念，重點在於既是最先進又是流行的方法。一個主要的見解是優化問題的純分析特性與用於解決該問題的算法行為之間的聯繫。每章末尾提供了練習題。

本書的內容分為三個部分。第一部分提供了線性規劃的自成體系的介紹。這部分的呈現相當傳統，涵蓋了線性規劃的基本理論、許多最有效的數值算法以及其重要的特殊應用。第二部分獨立於第一部分，涵蓋了無約束優化的理論，包括適當最優條件的推導和基本算法的介紹。本書的這一部分探討了算法的一般性質並定義了各種收斂的概念。接著，第三部分將第二部分中發展的概念擴展到有約束的優化問題。除了幾個孤立的章節外，這一部分也獨立於第一部分。因此，第二和第三部分可以在不閱讀第一部分的情況下輕鬆使用，事實上，許多大學已經以這種方式使用本書。

本版新增了數據科學和機器學習中的熱門主題，例如馬可夫決策過程、法卡斯引理、收斂速度分析、對偶理論及其應用、各種一階方法、隨機梯度法、鏡像下降法、Frank-Wolf方法、ALM/ADMM方法、非凸優化的內部信任區域方法、分佈魯棒優化、在線線性規劃、用於傳感器網絡定位的半正定規劃，以及非線性優化的不可行性檢測。

作者簡介

David G. Luenberger received his B.S. degree from the California Institute of Technology and his M.S. and Ph.D. degrees from Stanford University, all in Electrical Engineering. Since 1963 he has served on the faculty of Stanford University. He helped found the Department of Engineering-Economic Systems, which have since become the Department of Management Science and Engineering, where his is currently a professor.

He is a Member of the National Academy of Engineering (2008) and has received e.g. the Bode Lecture Prize of the Control Systems Society (1990), the Oldenburger Medal of the American Society of Mechanical Engineers (1995), and the Expository Writing Award of the Institute of Operations Research and Management Science (1999). He is a Fellow of the Institute of Electrical and Electronic Engineers (since 1975).

Yinyu Ye is currently the Kwoh-Ting Li Professor in the School of Engineering at the Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering. He received his B.S. degree in System Engineering from Huazhong University of Science and Technology, China, and his M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. He is an INFORMS (The Institute for Operations Research and The Management Science). Fellow since 2012, and has received several academic awards including: the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the 2015 SPS Signal Processing Magazine Best Paper Award, the winner of the 2014 SIAM Optimization Prize awarded (every three years), the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the inaugural 2006 Farkas Prize on Optimization, the 2009 IBM Faculty Award.

 

 

 

作者簡介(中文翻譯)

David G. Luenberger 於加州理工學院獲得學士學位，並在史丹佛大學獲得碩士及博士學位，皆為電機工程領域。自1963年以來，他一直在史丹佛大學任教。他協助創立了工程經濟系，該系後來成為管理科學與工程系，他目前是該系的教授。

他是美國國家工程院的成員（2008年），並曾獲得控制系統學會的Bode講座獎（1990年）、美國機械工程師學會的Oldenburger獎章（1995年）以及運籌學與管理科學學會的解說寫作獎（1999年）。他自1975年以來是電機電子工程師學會的會士。

Yinyu Ye 目前是管理科學與工程系及計算與數學工程研究所的Kwoh-Ting Li教授。他在中國華中科技大學獲得系統工程的學士學位，並在史丹佛大學獲得工程經濟系及運籌學的碩士和博士學位。他自2012年以來是INFORMS（運籌學與管理科學學會）的會士，並獲得多項學術獎項，包括：2009年約翰·馮·諾依曼理論獎，以表彰他在運籌學與管理科學理論方面的持續貢獻，2015年SPS信號處理雜誌最佳論文獎，2014年SIAM優化獎（每三年頒發一次）的得主，2012年ISMP Tseng講座獎（每三年頒發一次）以表彰他在連續優化方面的傑出貢獻，2006年Farkas優化獎，以及2009年IBM教職員獎。

類似商品