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001			9780429203152
003			FlBoTFG
005			20220724194421.0
006			m o d
007			cr cnu|||unuuu
008			191120s2020 flu ob 001 0 eng d
040			_aOCoLC-P _beng _erda _epn _cOCoLC-P
020			_a9780429203152 _q(electronic bk.)
020			_a0429203152 _q(electronic bk.)
020			_a9780429511738 _q(electronic bk. : PDF)
020			_a0429511736 _q(electronic bk. : PDF)
020			_a9780429515163 _q(electronic bk. : EPUB)
020			_a0429515162 _q(electronic bk. : EPUB)
020			_z9780367195571
035			_a(OCoLC)1128095579
035			_a(OCoLC-P)1128095579
050		4	_aQA402.5
072		7	_aBUS _x049000 _2bisacsh
072		7	_aMAT _x000000 _2bisacsh
072		7	_aMAT _x021000 _2bisacsh
072		7	_aPB _2bicssc
082	0	4	_a519.6 _223
100	1		_aChallal, Samia, _eauthor.
245	1	0	_aIntroduction to the theory of optimization in Euclidean space / _cSamia Challal, Glendon College-York University, Toronto, Canada.
264		1	_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c[2020]
264		4	_c©2020
300			_a1 online resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aSeries in operations research
500			_a"A Chapman & Hall book."
520			_aIntroduction to the Theory of Optimization in Euclidean Space is intended to provide students with a robust introduction to optimization in Euclidean space, demonstrating the theoretical aspects of the subject whilst also providing clear proofs and applications. Students are taken progressively through the development of the proofs, where they have the occasion to practice tools of differentiation (Chain rule, Taylor formula) for functions of several variables in abstract situations. Throughout this book, students will learn the necessity of referring to important results established in advanced Algebra and Analysis courses. Features Rigorous and practical, offering proofs and applications of theorems Suitable as a textbook for advanced undergraduate students on mathematics or economics courses, or as reference for graduate-level readers Introduces complex principles in a clear, illustrative fashion
505	0		_a1. Introduction 1.1. Formulation of some optimization problems 1.2. Particular subsets of Rn 1.3. Functions of several variables 2. Unconstrained Optimization 2.1. Necessary condition 2.2. Classification of local extreme points 2.3. Convexity/concavity and global extreme points 2.4. Extreme value theorem 3. Constrained Optimization-Equality constraints 3.1. Tangent plane 3.2. Necessary condition for local extreme points-Equality constraints 3.3. Classification of local extreme points-Equality constraints 3.4. Global extreme points-Equality constraints 4. Constrained Optimization-Inequality constraints 4.1. Cone of feasible directions 4.2. Necessary condition for local extreme points/Inequality constraints 4.3. Classification of local extreme points-Inequality constraints 4.4. Global extreme points-Inequality constraints 4.5. Dependence on parameters
588			_aOCLC-licensed vendor bibliographic record.
650		0	_aMathematical optimization.
650		0	_aEuclidean algorithm.
650		7	_aBUSINESS & ECONOMICS / Operations Research _2bisacsh
650		7	_aMATHEMATICS / General _2bisacsh
650		7	_aMATHEMATICS / Number Systems _2bisacsh
856	4	0	_3Read Online _uhttps://www.taylorfrancis.com/books/9780429203152
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942			_2lcc _cEBK
999			_c17388 _d17388