Description: The Projected Subgradient Algorithm in Convex Optimization by Alexander J. Zaslavski Estimated delivery 3-12 business days Format Paperback Condition Brand New Description The discussion takes into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for dierent steps are dierent, in general. Publisher Description This focused monograph presents a study of subgradient algorithms for constrained minimization problems in a Hilbert space. The book is of interest for experts in applications of optimization to engineering and economics. The goal is to obtain a good approximate solution of the problem in the presence of computational errors. The discussion takes into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for dierent steps are dierent, in general. The book is especially useful for the reader because it contains solutions to a number of difficult and interesting problems in the numerical optimization. The subgradient projection algorithm is one of the most important tools in optimization theory and its applications. An optimization problem is described by an objective function and a set of feasible points. For this algorithm each iteration consists of two steps. The first step requires a calculation of a subgradient of the objective function; the second requires a calculation of a projection on the feasible set. The computational errors in each of these two steps are different. This book shows that the algorithm discussed, generates a good approximate solution, if all the computational errors are bounded from above by a small positive constant. Moreover, if computational errors for the two steps of the algorithm are known, one discovers an approximate solution and how many iterations one needs for this. In addition to their mathematical interest, the generalizations considered in this book have a significant practical meaning. Author Biography Alexander J. Zaslavski is professor in the Department of Mathematics, Technion-Israel Institute of Technology, Haifa, Israel. Details ISBN 3030602990 ISBN-13 9783030602994 Title The Projected Subgradient Algorithm in Convex Optimization Author Alexander J. Zaslavski Format Paperback Year 2020 Pages 146 Edition 1st Publisher Springer Nature Switzerland AG GE_Item_ID:137653416; 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: 9783030602994
Book Title: The Projected Subgradient Algorithm in Convex Optimization
Number of Pages: VI, 146 Pages
Publication Name: Projected Subgradient Algorithm in Convex Optimization
Language: English
Publisher: Springer International Publishing A&G
Subject: Numerical Analysis, Optimization
Publication Year: 2020
Type: Textbook
Item Weight: 16 Oz
Author: Alexander J. Zaslavski
Item Length: 9.3 in
Subject Area: Mathematics
Item Width: 6.1 in
Series: Springerbriefs in Optimization Ser.
Format: Trade Paperback