In the new edition of this student text, the author has made substantial revisions and additions to enhance the book's usefulness without destroying its character as a lucid and readable text. Most economics courses separate the teaching of the mathematics of constrained maximization from its economic applications. The aim of this book is to provide an integrated treatment of optimization that relates mathematics to economics from the outset, thus facilitating a quicker and deeper understanding. Proofs of the mathematical therorems are structured to bring out points of economic interest and to enable economic applications. The illustrative examples are also chosen for their economic interest and usefulness and suggestions for further reading are provided at the end of each chapter. This new edition has been revised to accommodate the siginificant changes the subject has undergone since the publication of the first edition. A chapter on uncertainty has been added with treatment of topics such as finance and asymmetric information, and the chapter on dynamic programmming has been expanded.

"The true merit of this book, however, lies in its pedagogical qualities which are so impressive..." "Throughout the book, the authors make serious efforts to give geometric and intuitive explanations of various algebraic concepts, and they are widely successful in this effort." "In conclusion, this is an outstanding textbook that presents linear optimization in a truly modern and up-to-date light. One reading of this book is sufficient to appreciate the tremendous amount of quality effort that the authors have put into the writing, and I strongly recommend it to all teachers, researchers and practitioners of mathematical programming." --Motakuri Ramana in Optima, Issue 54 Bertsimas and Tsitsiklis have written a comprehensive treatise, offering an easy-to-understand presentation of linear programming and related topics, including network-flow programming and discrete optimization. --Jonathan Bard in Interfaces, Issue 30(4), July 2000

《凸优化理论(影印版)》作者德梅萃·博赛克斯教授是优化理论的国际著名学者、美国国家工程院院士，现任美国麻省理工学院电气工程与计算机科学系教授，曾在斯坦福大学工程经济系和伊利诺伊大学电气工程系任教，在优化理论、控制工程、通信工程、计算机科学等领域有丰富的科研教学经验，成果丰硕。博赛克斯教授是一位多产作者，著有14本专著和教科书。《凸优化理论(影印版)》是作者在优化理论与方法的系列专著和教科书中的一本，自成体系又相互对应。主要内容分为两部分：凸分析和凸问题的对偶优化理论。

本书作者现任美国西北大学教授，多种国际权威杂志的主编、副主编。作者根据在教学、研究和咨询中的经验，写了这本适合学生和实际工作者的书。本书提供连续优化中大多数有效方法的全面的最新的论述。每一章从基本概念开始，逐步阐述当前可用的最佳技术。　　本书强调实用方法，包含大量图例和练习，适合广大读者阅读，可作为工程、运筹学、数学、计算机科学以及商务方面的研究生教材，也可作为该领域的科研人员和实际工作人员的手册。　　总之，作者力求本书阅读性强，内容丰富，论述严谨，能揭示数值最优化的美妙本质和实用价值。

最优化理论与算法（第2版），ISBN：9787302113768，作者：陈宝林 编著

Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It responds to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.Drawing on their experiences in teaching, research, and consulting, the authors have produced a textbook that will be of interest to students and practitioners alike. Each chapter begins with the basic concepts and builds up gradually to the best techniques currently available.Because of the emphasis on practical methods, as well as the extensive illustrations and exercises, the book is accessible to a wide audience. It can be used as a graduate text in engineering, operations research, mathematics, computer science, and business. It also serves as a handbook for researchers and practitioners in the field.Above all, the authors have strived to produce a text that is pleasant to read, informative, and rigorous - one that reveals both the beautiful nature of the discipline and its practical side.MMOR Mathematical Methods of Operations Research, 2001: "The book looks very suitable to be used in an graduate-level course in optimization for students in mathematics, operations research, engineering, and others. Moreover, it seems to be very helpful to do some self-studies in optimization, to complete own knowledge and can be a source of new ideas.... I recommend this excellent book to everyone who is interested in optimization problems."