Introduction | p. 1 |
Some Issues in Linear Computation | p. 7 |
Three Examples of Linear Computation | p. 13 |
Gargantuan Liquids, Inc | p. 13 |
Oil Refineries, bpd | p. 15 |
Save Berlin, usw | p. 20 |
The Linear Programming Problem | p. 25 |
Standard and Canonical Forms | p. 26 |
Matrices, Vectors, Scalars | p. 27 |
Basic Concepts | p. 33 |
A Fundamental Theorem | p. 36 |
Notational Conventions and Illustrations | p. 39 |
Five Preliminaries | p. 43 |
Bases and Basic Feasible Solutions | p. 43 |
Detecting Optimality | p. 43 |
Detecting Unboundedness | p. 44 |
A Rank-One Update | p. 45 |
Changing Bases | p. 45 |
Simplex Algorithms | p. 49 |
Notation, Reading Instructions, Updating | p. 50 |
Big M or How to Get Started | p. 54 |
Selecting a Pivot Row and Column | p. 56 |
Data Structures, Tolerances, Product Form | p. 58 |
Equation Format and Cycling | p. 63 |
Finiteness of a Simplex Algorithm | p. 69 |
Canonical Form | p. 71 |
A Worst-Case Example for a Simplex Algorithm | p. 75 |
Block Pivots and Structure | p. 77 |
A Generalized Product Form | p. 79 |
Upper Bounds | p. 82 |
Primal-Dual Pairs | p. 87 |
Weak Duality | p. 89 |
Strong Duality | p. 91 |
Economic Interpretation and Applications | p. 94 |
Solvability, Redundancy, Separability | p. 97 |
A Dual Simplex Algorithm | p. 103 |
Correctness, Finitenoss, Initialization | p. 105 |
Post-Optimality | p. 109 |
A Dynamic Simplex Algorithm | p. 114 |
Analytical Geometry | p. 121 |
Points, Linos, Subspaces | p. 124 |
Polyhedra, Ideal Descriptions, Cones | p. 131 |
Faces, Valid Equations, Affine Hulls | p. 134 |
Facets, Minimal Complete Descriptions, Quasi-Uniqueness | p. 138 |
Asymptotic Cones and Extreme Rays | p. 141 |
Adjacency I, Extreme Rays of Polyhedra, Homogenization | p. 144 |
Point Sets, Affine Transformations, Minimal Generators | p. 147 |
Displaced Cones, Adjacency II, Images of Polyhedra | p. 150 |
Carathéodory, Minkowski, Weyl | p. 155 |
Minimal Generators, Canonical Generators, Quasi-Uniqueness | p. 157 |
Double Description Algorithms | p. 165 |
Correctness and Finitenoss of the Algorithm | p. 168 |
Geometry, Euclidean Reduction, Analysis | p. 173 |
The Basis Algorithm and All-Integer Inversion | p. 180 |
An All-Integer Algorithm for Double Description | p. 183 |
Digital Sizes of Rational Polyhedra and Linear Optimization | p. 188 |
Facet Complexity, Vertex Complexity, Complexity of Inversion | p. 190 |
Polyhedra and Related Polytopes for Linear Optimization | p. 194 |
Feasibility, Binary Search, Linear Optimization | p. 197 |
Perturbation, Uniqueness, Separation | p. 202 |
Geometry and Complexity of Simplex Algorithms | p. 207 |
Pivot Column Choice, Simplex Paths, Big M Revisited | p. 208 |
Gaussian Elimination, Fill-In, Scaling | p. 212 |
Iterative Step I, Pivot Choice, Cholesky Factorization | p. 216 |
Cross Multiplication, Iterative Step II, Integer Factorization | p. 219 |
Division Free Gaussian Elimination and Cramer's Rule | p. 221 |
Circles, Spheres, Ellipsoids | p. 229 |
Projective Algorithms | p. 239 |
A Basic Algorithm | p. 243 |
The Solution of the Approximate Problem | p. 245 |
Convergence of the Approximate Iterates | p. 246 |
Correctness, Finiteness, Initialization | p. 250 |
Analysis, Algebra, Geometry | p. 253 |
Solution to the Problem in the Original Space | p. 254 |
The Solution in the Transformed Space | p. 260 |
Geometric Interpretations and Properties | p. 264 |
Extending the Exact Solution and Proofs | p. 268 |
Examples of Projective Images | p. 271 |
The Cross Ratio | p. 274 |
Reflection on a Circle and Sandwiching | p. 278 |
The Iterative Step | p. 283 |
A Projective Algorithm | p. 288 |
Centers, Barriers, Newton Steps | p. 292 |
A Method of Centers | p. 296 |
The Logarithmic Barrier Function | p. 298 |
A Newtonian Algorithm | p. 303 |
Coda | p. 308 |
Ellipsoid Algorithms | p. 309 |
Matrix Norms, Approximate Inverses, Matrix Inequalities | p. 316 |
Ellipsoid "Halving" in Approximate Arithmetic | p. 320 |
Polynomial-Time Algorithms for Linear Programming | p. 328 |
Linear Programming and Binary Search | p. 336 |
Deep Cuts, Sliding Objective, Large Steps, Line Search | p. 339 |
Linear Programming the Ellipsoidal Way: Two Examples | p. 344 |
Correctness and Finiteness of the DCS Ellipsoid Algorithm | p. 348 |
Optimal Separators, Most Violated Separators, Separation | p. 352 |
¿-Solidification of Flats, Polytopal Norms, Rounding | p. 356 |
Rational Rounding and Continued Fractions | p. 361 |
Optimization and Separation | p. 368 |
¿-Optimal Sets and ¿-Optimal Solutions | p. 371 |
Finding Direction Vectors in the Asymptotic Cone | p. 373 |
A CCS Ellipsoid Algorithm | p. 375 |
Linear Optimization and Polyhedral Separation | p. 378 |
Combinatorial Optimization: An Introduction | p. 387 |
The Berlin Airlift Model Revisited | p. 389 |
Complete Formulations and Their Implications | p. 396 |
Extremal Characterizations of Ideal Formulations | p. 405 |
Blocking and Antiblocking Polyhedra | p. 414 |
Polyhedra with the Integrality Property | p. 417 |
Appendices | |
Short-Term Financial Management | p. 423 |
Operations Management in a Refinery | p. 427 |
Automatized Production: PCBs and Ulysses' Problem | p. 441 |
References | p. 457 |
Bibliography | p. 479 |
Index | p. 495 |
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