Heckman C.C. Linear Programming: Beyond 4.2(Simplex Method)

W.H. Freeman, 1983. - 485 pages. This book include some background in linear algebra and some experience with proof based mathematics. It makes a good subject for students to study as they are developing proof writing skills. The first 10 chapters of the book present the simplex method, the revised simplex method, duality theory, and sensitivity analysis. The remaining chapters of the book are largely independent, mostly focused on various...

Springer – 2003, 474 pages Linear Programming 2 continues where Linear Programming 1 left o?. We assume that the reader has an introductory knowledge of linear programming, for example has read Linear Programming 1: Introduction (or its equivalent) and has knowledge of linear algebra (reviewed in the appendices in Linear Programming 1). In this volume, we prove all theorems stated and those that were sketched but not proved in Linear Programming...

Contents. Introduction. Optimization with Multiple Criteria. Decision Space and Objective (Criterion) Space. Notions of Optimality. Orders and Cones. Classification of Multicriteria Optimization Problems. Efficiency and Nondominance. Efficient Solutions and Nondominated Points. Bounds on the Nondominated Set. Weakly and Strictly Efficient Solutions. Proper Efficiency and Proper Nondominance. The Weighted Sum Method and Related Topics. Weighted Su...

Publisher: Springer | 2007 | ISBN10: 3540736700 | 380 pages Based on earlier work by a variety of authors in the 1930s and 1940s, the simplex method for solving linear programming problems was developed in 1947 by the American mathematician George B. Dantzig. Helped by the computer revolution, it has been described by some as the overwhelmingly most significant mathematical development of the last century. Owing to the simplex method, linear prog...

Publisher: Society for Industrial Mathematics | 2008 | ISBN10: 0898716438 | 280 pages MPS-SIAM Series on Optimization This textbook provides a self-contained introduction to linear programming using MATLAB® software to elucidate the development of algorithms and theory. Early chapters cover linear algebra basics, the simplex method, duality, the solving of large linear problems, sensitivity analysis, and parametric linear programming. In later ch...

Springer-Verlag Berlin Heidelberg, 2007. 226 p. What Is It, and What For? A Linear Program. What Can Be Found in This Book. Linear Programming and Linear Algebra. Significance and History of Linear Programming. Examples. Optimized Diet: Wholesome and Cheap? Flow in a Network. ce Cream All Year Round. Fitting a Line. Separation of Points. Largest Disk in a Convex Polygon. Cutting Paper Rolls. nteger Programming and LP Relaxation. nteger Programmin...

John Wiley & Sons, 2009. 813 p. 4th ed. ISBN 978-0-470-18352-6. Contents. Preface. Introduction to Optimization. Classical Optimization Techniques. Linear Programming I: Simplex Method. Linear Programming II: Additional Topics and Extensions. Nonlinear Programming I: One-Dimensional Minimization Methods. Nonlinear Programming II: Unconstrained Optimization Techniques. Nonlinear Programming III: Constrained Optimization Techniques. Geometric P...

Acаdemic Prеss, 1993. - 568 pages. This book gives a complete, concise introduction to the theory and applications of linear programming. It emphasizes the practical applications of mathematics, and makes the subject more accessible to individuals with varying mathematical abilities. It is one of the first rigorous linear programming texts that does not require linear algebra as a prerequisite. In addition, this text contains a floppy disk cont...

Princeton University, 2001, -466 pp. This book is about constrained optimization. It begins with a thorough treatment of linear programming and proceeds to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Along the way, dynamic programming and the linear complementarity problem are touched on as well. The book aims to be a first introduction to the subject. Specific examples and concrete algori...

Publisher: Springer; 3rd ed. Edition | 2007 | ISBN10: 0387743871 | 464 pages Linear Programming: Foundations and Extensions is an introduction to the field of optimization. The book emphasizes constrained optimization, beginning with a substantial treatment of linear programming, and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written. Specific examples...