This book presents a unified, progressive treatment of the basic mathematical tools of mathematical programming theory. The subject of (static) optimization, also called mathematical programming, is one of the most important and widespread branches of modern mathematics, serving as a cornerstone of such scientific subjects as economic analysis, operations research, management sciences, engineering, chemistry, physics, statistics, computer science, biology, and social sciences. This book presents a unified, progressive treatment of the basic mathematical tools of mathematical programming theory. The authors expose said tools, along with results concerning the most common mathematical programming problems formulated in a finite-dimensional setting, forming the basis for further study of the basic questions on the various algorithmic methods and the most important particular applications of mathematical programming problems. This book assumes no previous experience in optimization theory, and the treatment of the various topics is largely self-contained. Prerequisites are the basic tools of differential calculus for functions of several variables, the basic notions of topology in Rn and of linear algebra, and the basic mathematical notions and theoretical background used in analyzing optimization problems. The book is aimed at both undergraduate and postgraduate students interested in mathematical programming problems but also those professionals who use optimization methods and wish to learn the more theoretical aspects of these questions.
The subject of (static) optimization, also called mathematical programming, is one of the most important and widespread branches of modern mathematics, serving as a cornerstone of such scientific subjects as economic analysis, operations research, management sciences, engineering, chemistry, physics, statistics, computer science, biology, and social sciences. This book presents a unified, progressive treatment of the basic mathematical tools of mathematical programming theory. The authors expose said tools, along with results concerning the most common mathematical programming problems formulated in a finite-dimensional setting, forming the basis for further study of the basic questions on the various algorithmic methods and the most important particular applications of mathematical programming problems. This book assumes no previous experience in optimization theory, and the treatment of the various topics is largely self-contained. Prerequisites are the basic tools of differential calculus for functions of several variables, the basic notions of topology and of linear algebra, and the basic mathematical notions and theoretical background used in analyzing optimization problems. The book is aimed at both undergraduate and postgraduate students interested in mathematical programming problems but also those professionals who use optimization methods and wish to learn the more theoretical aspects of these questions.
Puts forth a modern approach to the most valuable mathematical tools within mathematical programming theory Forms the basis for further study of various algorithmic methods and applications of mathematical programming problems Aids courses dedicated to optimization, economic analysis, and others related to optimization theory and its methods
Giorgio Giorgi
mathematical optimization graduate textbook Convex Analysis Operations Research and Management Science mathematical programming textbook duality theory of mathematical programming problems linear algebra constraint abstract problem convex programming problem Linear Programming Quadratic Programming vector optimization problem
“This book serves as a comprehensive and indispensable tool for Ph.D. students and young researchers in the Field of nonlinear programming. … it offers a substantial coverage of theoretical results concerning optimality conditions in nonlinear programming. Certain chapters are particularly valuable as teaching materials for advanced master's courses.” (Giovanni Fasano, Mathematical Reviews, Decemeber, 2024)