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...
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."
作者简介
· · · · · ·
Jorge Nocedal
ECE Department, Northwestern University, Evanston, USA
Stephen J. Wright
Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, USA
It (BFGS) is also more numerically stable, and has very effective “self-correcting
properties” not shared by DFP, which may account for its superior performance in practice. (查看原文)
In a sense, the line search and trust-region approaches differ in the order in which they
choose the direction and distance of the move to the next iterate. Line search starts by fixing the direction pk and then identifying an appropriate distance, namely the step length αk . In trust region, we first choose a maximum distance—the trust-region radius k —and then seek a direction and step that attain the best improvement possible subject to this distance constraint. If this step proves to be unsatisfactory, we reduce the distance measure k and try again. (查看原文)
Springer Series in Operations Research(共21册)，
这套丛书还有
《Finite-Dimensional Variational Inequalities and Complementarity Problems》《Facility Location》《Discrete-event Simulation》《Linear Programming 1》《Stochastic Petri Nets》
等
。
摇摆过客
vgaas
科学出版社2006版
1 有用 长安 2014-09-28 11:40:04
惭愧当时学的时候没有好好学，感觉这本教材很权威也有难度，信赖域算法就一直没理解。
1 有用 Luke 2017-10-24 00:16:34
真的很重要，没事要多翻一翻的书
1 有用 可乐音 2009-09-13 15:29:16
more comprehensive and practical?
0 有用 xlabatery 2023-02-18 14:45:14 美国
比较工程和应用向，证明比较少
1 有用 Shaquille 2013-07-05 13:50:23
看了快两遍了，还是不知道看的啥，我类个去！