The preface and table of contents of the book "Introduction to Linear Optimization" by Dimitris Bertsimas and John N. Tsitsiklis provide an overview of the content, which is divided into several chapters covering various aspects of linear optimization. The book begins with an introduction to the linear programming problem, including its variants, examples, and graphical representation. It then delves into the geometry of linear programming, discussing polyhedra, convex sets, and the simplex method. The simplex method is explored in detail, including its optimality conditions, implementations, and computational efficiency. The book also covers duality theory, sensitivity analysis, large-scale optimization techniques, network flow problems, and the complexity of linear programming. Additionally, it discusses interior point methods, integer programming formulations and methods, and the practical applications of linear optimization in various real-world problems. The book concludes with a discussion on the art of linear optimization, including modeling languages, libraries, and specific case studies.The preface and table of contents of the book "Introduction to Linear Optimization" by Dimitris Bertsimas and John N. Tsitsiklis provide an overview of the content, which is divided into several chapters covering various aspects of linear optimization. The book begins with an introduction to the linear programming problem, including its variants, examples, and graphical representation. It then delves into the geometry of linear programming, discussing polyhedra, convex sets, and the simplex method. The simplex method is explored in detail, including its optimality conditions, implementations, and computational efficiency. The book also covers duality theory, sensitivity analysis, large-scale optimization techniques, network flow problems, and the complexity of linear programming. Additionally, it discusses interior point methods, integer programming formulations and methods, and the practical applications of linear optimization in various real-world problems. The book concludes with a discussion on the art of linear optimization, including modeling languages, libraries, and specific case studies.