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Introduction to nonlinear optimizati...
~
Beck, Amir.
Introduction to nonlinear optimization : = theory, algorithms, and applications with MATLAB /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Introduction to nonlinear optimization :/ Amir Beck.
Reminder of title:
theory, algorithms, and applications with MATLAB /
Author:
Beck, Amir.
Published:
Philadelphia :Society for Industrial and Applied Mathematics : : c2014.,
Description:
xii, 282 p. :ill. (chiefly col.) ; : 26 cm.;
Subject:
Mathematical optimization. -
Online resource:
http://www.loc.gov/catdir/enhancements/fy1503/2014029493-b.html
Online resource:
http://www.loc.gov/catdir/enhancements/fy1503/2014029493-d.html
Online resource:
http://www.loc.gov/catdir/enhancements/fy1503/2014029493-t.html
ISBN:
9781611973648 (pbk.) :
Introduction to nonlinear optimization : = theory, algorithms, and applications with MATLAB /
Beck, Amir.
Introduction to nonlinear optimization :
theory, algorithms, and applications with MATLAB /Amir Beck. - Philadelphia :Society for Industrial and Applied Mathematics :c2014. - xii, 282 p. :ill. (chiefly col.) ;26 cm. - MOS-SIAM series on optimization.
Includes bibliographical references (p. 277-279) and index.
Mathematical preliminaries -- Optimality conditions for unconstrained optimization -- Least squares -- The gradient method -- Newton's method -- Convex sets -- Convex functions -- Convex optimization -- Optimization over a convex set -- Optimality conditions for linearly constrained problems -- The KKT conditions -- Duality.
ISBN: 9781611973648 (pbk.) :NT3256
LCCN: 2014029493Subjects--Uniform Titles:
MATLAB.
Subjects--Topical Terms:
527675
Mathematical optimization.
LC Class. No.: QA402.5 / .B4224 2014
Dewey Class. No.: 519.6
Introduction to nonlinear optimization : = theory, algorithms, and applications with MATLAB /
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Introduction to nonlinear optimization :
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xii, 282 p. :
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ill. (chiefly col.) ;
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Includes bibliographical references (p. 277-279) and index.
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Mathematical preliminaries -- Optimality conditions for unconstrained optimization -- Least squares -- The gradient method -- Newton's method -- Convex sets -- Convex functions -- Convex optimization -- Optimization over a convex set -- Optimality conditions for linearly constrained problems -- The KKT conditions -- Duality.
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