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"This compact book, through the simplifying perspective it presents, will take a reader who knows little of interior-point methods to within sight of the research frontier, developing key ideas that were over a decade in the making by numerous interior-point method researchers. It aims at developing a thorough understanding of the most general theory for interior-point methods, a class of algorithms for convex optimization problems. The study of these algorithms has dominated the continuous optimization literature for nearly 15 years. In that time, the theory has matured tremendously, but much of the literature is difficult to understand, even for specialists. By focusing only on essential elements of the theory and emphasizing the underlying geometry, A Mathematical View of Interior-Point Methods in Convex Optimization makes the theory accessible to a wide audience, allowing them to quickly develop a fundamental understanding of the material.The author begins with a general presentation of material pertinent to continuous optimization theory, phrased so as to be readily applicable in developing interior-point method theory. This presentation is written in such a way that even motivated Ph.D. students who have never had a course on continuous optimization can gain sufficient intuition to fully understand the deeper theory that follows. Renegar continues by developing the basic interior-point method theory, with emphasis on motivation and intuition. In the final chapter, he focuses on the relations between interior-point methods and duality theory, including a self-contained introduction to classical duality theory for conic programming; an exploration of symmetric cones; and the development of the general theory of primal-dual algorithms for solving conic programming optimization problems.Rather than attempting to be encyclopedic, A Mathematical View of Interior-Point Methods in Convex Optimization gives the reader a solid understanding of the core concepts and relations, the kind of understanding that stays with a reader long after the book is finished."

"Provides a relatively brief introduction to conjugate duality in both finite- and infinite-dimensional problems. An emphasis is placed on the fundamental importance of the concepts of Lagrangian function, saddle-point, and saddle-value. General examples are drawn from nonlinear programming, approximation, stochastic programming, the calculus of variations, and optimal control."

"Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.Lectures on Modern Convex Optimization: Analysis, Algorithms, and Engineering Applications presents and analyzes numerous engineering models, illustrating the wide spectrum of potential applications of the new theoretical and algorithmical techniques emerging from the significant progress taking place in convex optimization. It is hoped that the information provided here will serve to promote the use of these techniques in engineering practice. The book develops a kind of "algorithmic calculus" of convex problems, which can be posed as conic quadratic and semidefinite programs. This calculus can be viewed as a "computationally tractable" version of the standard convex analysis."

"No one working in duality should be without a copy of Convex Analysis and Variational Problems. This book contains different developments of infinite dimensional convex programming in the context of convex analysis, including duality, minmax and Lagrangians, and convexification of nonconvex optimization problems in the calculus of variations (infinite dimension). It also includes the theory of convex duality applied to partial differential equations; no other reference presents this in a systematic way. The minmax theorems contained in this book have many useful applications, in particular the robust control of partial differential equations in finite time horizon. First published in English in 1976, this SIAM Classics in Applied Mathematics edition contains the original text along with a new preface and some additional references."

"This book provides a self-contained presentation of basic results of the theory of convex sets and functions in infinite-dimensional spaces. The main emphasis is on applications to convex optimization and convex optimal control problems in Banach spaces. A distinctive feature is a strong emphasis on the connection between theory and application. This edition has been updated to include new results pertaining to advanced concepts of subdifferential for convex functions and new duality results in convex programming. The last chapter, concerned with convex control problems, has been rewritten and completed with new research concerning boundary control systems, the dynamic programming equations in optimal control theory and periodic optimal control problems. "

"Discrete Convex Analysis is a novel paradigm for discrete optimization that combines the ideas in continuous optimization (convex analysis) and combinatorial optimization (matroid/submodular function theory) to establish a unified theoretical framework for nonlinear discrete optimization. The study of this theory is expanding with the development of efficient algorithms and applications to a number of diverse disciplines like matrix theory, operations research, and economics. This self-contained book is designed to provide a novel insight into optimization on discrete structures and should reveal unexpected links among different disciplines. It is the first and only English-language monograph on the theory and applications of discrete convex analysis."

"The aim of this monograph is to present a self-contained introduction to some geometric and analytic aspects of the Yamabe problem. The book also describes a wide range of methods and techniques that can be successfully applied to nonlinear differential equations in particularly challenging situations. Such situations occur where the lack of compactness, symmetry and homogeneity prevents the use of more standard tools typically used in compact situations or for the Euclidean setting. After a self-contained treatment of the geometric tools used in the book, readers are introduced to the main subject by means of a concise but clear study of some aspects of the Yamabe problem on compact manifolds. This study provides the motivation and geometrical feeling for the subsequent part of the work. In the main body of the book, it is shown how the geometry and the analysis of nonlinear partial differential equations blend together to give up-to-date results on existence, nonexistence, uniqueness and a priori estimates for solutions of general Yamabe-type equations and inequalities on complete, non-compact Riemannian manifolds."

"Fungsi konveks merupakan salah satu topik di analisis yang berkaitan erat dengan teori pertidaksamaan. Lebih lanjut, definisi fungsi konveks memiliki perluasan, yaitu fungsi s-konveks jenis pertama dan jenis kedua, untuk s elemen 0,1] tetap. Fungsi konveks berkaitan dengan pertidaksamaan Hermite-Hadamard-Fejer, yangmerupakan pertidaksamaan integral yang melibatkan fungsi konveks. Pengembangan lebih lanjut dari pertidaksamaan tersebut dilakukan dengan melibatkan fungsi s-konveks dan juga melalui konsep integral fraksional. Dalam skripsi ini dibahas bentuk-bentuk pertidaksamaan tipe Hermite-Hadamard-Fej ryang berlaku untuk fungsi s-konveks jenis kedua melalui integral fraksional Riemann-Liouville. Dari hasil tersebut diperoleh hubungan antara pertidaksamaan yang diperoleh dengan pertidaksamaan yang sama untuk fungsi konveks.

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The convex function is one of the topics in mathematics that is closely related to the theory of inequality. Furthermore, the definition of convex function has an extension which is the first and second kind of s convex function, for fixed s elemen 0,1 . Convex function has a relation to the Hermite Hadamard Fejerinequality, which is an integral inequality involving a convex function. Further development of these inequalities involves the s convex function and also through the concept of fractional integral. In this study, we discuss theHermite Hadamard Fej r type inequality that applies to the second kind of s convex function via the Riemann Liouville fractional integral. From these results, the relationship between these inequalities with the same type of inequality for convex function, are obtained."

"Pertidaksamaan Hadamard adalah pertidaksamaan yang dibentuk oleh integral Riemann suatu fungsi konveks pada interval tertutup dengan integrasi numerik aturan titik tengah dan aturan trapesium. Hasil pengembangan dari pertidaksamaan Hadamard untuk fungsi terturunkan dan perkalian dua fungsi disebut pertidaksamaan tipe Hadamard. Studi literatur ini bertujuan untuk mempelajari beberapa pertidaksamaan tipe Hadamard berkaitan dengan fungsi-konveksi.

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Hadamard's inequality is formed by Riemann integral form of convex function and its approximation rules by using midpoint rule and trapezoidal rule. The extension of Hadamard?s inequality for differentiable function and products of two functions is called Hadamard type. This study of literature is studying about the Hadamard type inequalities based on s-convexity."