Description: Lagrange-Type Functions in Constrained Non-Convex Optimization, Hardcover by Rubinov, Aleksandr Moiseevich; Yang, Xiaoqi, ISBN 1402076274, ISBN-13 9781402076275, Like New Used, Free shipping in the US Lagrange and penalty function methods can be used for studying nonconvex constrained optimization problems, but need to be generalized in order to obtain ways to reduce constrained optimization problems to suitably broad unconstrained ones. Rubinov (School of Information Technology and Mathematical Sciences, U. of Ballarat) and Yang (applied mathematics, Hong Kong Polytechnic U., China) explore a number of approaches towards such schemes, including nonlinear convolutions of the objective and constraint functions of the problem and the application of augmented Lagrangians constructed by means of general dualizing parameterizations. Annotation ©2004 Book News, Inc., Portland, OR ()
Price: 123.29 USD
Location: Jessup, Maryland
End Time: 2024-12-29T09:27:53.000Z
Shipping Cost: 0 USD
Product Images
Item Specifics
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 14 Days
Refund will be given as: Money Back
Return policy details:
Book Title: Lagrange-Type Functions in Constrained Non-Convex Optimization
Number of Pages: Xiv, 286 Pages
Publication Name: Lagrange-Type Functions in Constrained Non-Convex Optimization
Language: English
Publisher: Springer
Subject: Operations Research, Management Science, Optimization
Publication Year: 2003
Type: Textbook
Item Weight: 46.9 Oz
Subject Area: Mathematics, Business & Economics
Author: Aleksandr Moiseevich Rubinov, Xiaoqi Yang
Item Length: 9.3 in
Series: Applied Optimization Ser.
Item Width: 6.1 in
Format: Hardcover
