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Introduction 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.



 



Introduction 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


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    Arvustused

    "The textbook is relatively compact and written in a lecture note style that would be suitable for either a course or an independent study. Each mathematical theorem and its proof are complemented by examples and exercises that are mostly concrete and computational. [ . . .] This book distinguishes itself among undergraduate optimization books by organically picking up where multivariable calculus leaves off, with regards to both topic selection and level of rigor and abstraction." MAA Reviews

    "This book fills in the gap between the advanced, theoretical books on abstract Hilbert spaces, and the more practical books intended for Engineers, where theorems lack proofs. The author presents many theorems, along with their proofs, in a simple way and provides many examples and graphical illustrations to allow students grasp the material in an easy and quick way." Professor Salim Aissa Salah Messaoudi, University of Sharjah, UAE

    "This book, part of the CRC Series on Operations Research, is designed for undergraduate courses in operations research and mathematics. It starts at a fairly basic level, with open and closed sets, functions of more than one variable, surfaces in three dimensions, partial differentiation.

    The book is well produced. [ . . .] It is worth consideration as a text for appropriate courses" Mathematical Gazette "This book fills in the gap between the advanced, theoretical books on abstract Hilbert spaces, and the more practical books intended for Engineers, where theorems lack proofs. The author presents many theorems, along with their proofs, in a simple way and provides many examples and graphical illustrations to allow students grasp the material in an easy and quick way."

    Professor Salim Aissa Salah Messaoudi, University of Sharjah, UAE

    1. 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.
    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.
    Samia Challal is an assistant professor of Mathematics at Glendon College, the bilingual campus of York University. Her research interests include, homogenization, optimization, free boundary problems, partial differential equations, and problems arising from mechanics.