Description: Nonlinear Conjugate Gradient Methods for Unconstrained Optimization by Neculai Andrei Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. Publisher Description Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods, showing their properties and convergence characteristics as well as their performance in solving large-scale unconstrained optimization problems and applications. Comparisons to the limited-memory and truncated Newton methods are also discussed. Topics studied in detail include: linear conjugate gradient methods, standard conjugate gradient methods, acceleration of conjugate gradient methods, hybrid, modifications of the standard scheme, memoryless BFGS preconditioned, and three-term. Other conjugate gradient methods with clustering the eigenvalues or with the minimization of the condition number of the iteration matrix, are also treated. For each method, the convergence analysis, the computational performances and thecomparisons versus other conjugate gradient methods are given. The theory behind the conjugate gradient algorithms presented as a methodology is developed with a clear, rigorous, and friendly exposition; the reader will gain an understanding of their properties and their convergence and will learn to develop and prove the convergence of his/her own methods. Numerous numerical studies are supplied with comparisons and comments on the behavior of conjugate gradient algorithms for solving a collection of 800 unconstrained optimization problems of different structures and complexities with the number of variables in the range [1000,10000]. The book is addressed to all those interested in developing and using new advanced techniques for solving unconstrained optimization complex problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master students in mathematical programming, will find plenty of information and practical applications for solving large-scale unconstrained optimization problems and applications by conjugate gradient methods. Author Biography Neculai Andrei holds a position at the Center for Advanced Modeling and Optimization at the Academy of Romanian Scientists in Bucharest, Romania. Dr. Andreis areas of interest include mathematical modeling, linear programming, nonlinear optimization, high performance computing, and numerical methods in mathematical programming. In addition to this present volume, Neculai Andrei has published 2 books with Springer including Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology (2017) and Nonlinear Optimization Applications Using the GAMS Technology (2013). Details ISBN 3030429490 ISBN-13 9783030429492 Title Nonlinear Conjugate Gradient Methods for Unconstrained Optimization Author Neculai Andrei Format Hardcover Year 2020 Pages 498 Edition 1st Publisher Springer Nature Switzerland AG GE_Item_ID:158475121; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
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ISBN-13: 9783030429492
Book Title: Nonlinear Conjugate Gradient Methods for Unconstrained Optimizati
Number of Pages: Xxviii, 498 Pages
Publication Name: Nonlinear Conjugate Gradient Methods for Unconstrained Optimization
Language: English
Publisher: Springer International Publishing A&G
Subject: Applied, Optimization
Publication Year: 2020
Item Weight: 33.5 Oz
Type: Textbook
Subject Area: Mathematics
Author: Neculai Andrei
Item Length: 9.3 in
Item Width: 6.1 in
Series: Springer Optimization and Its Applications Ser.
Format: Hardcover
