Mathematical Programming: Theory and Methods, by S. M. Sinha

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Chapter 1 - Introduction, Pages 1-9
· Part - 1: Mathematical Foundations
· Chapter 2 - Basic theory of sets and functions, Pages 13-25
· Chapter 3 - Vector spaces, Pages 26-37
· Chapter 4 - Matrices and determinants, Pages 38-49
· Chapter 5 - Linear transformations and rank, Pages 50-55
· Chapter 6 - Quadratic forms and Eigenvalue problems, Pages 56-62
· Chapter 7 - Systems of linear equations and linear inequalities, Pages 63-
75
· Chapter 8 - Convex sets and convex cones, Pages 76-93
· Chapter 9 - Convex and concave functions, Pages 94-114
· Chapter 10 - Linear programming problems, Pages 117-131
· Chapter 11 - Simplex method: Theory and computation, Pages 132-144
   Chapter 12 - Simplex method: Initial basic feasible solution, Pages 145-157
· Chapter 13 - Degeneracy in linear programming, Pages 158-164
· Chapter 14 - The revised simplex method, Pages 165-176
· Chapter 15 - Duality in Linear Programming, Pages 177-198
· Chapter 16 - Variants of the simplex method, Pages 199-221
· Chapter 17 - Post-optimization problems: Sensitivity analysis and
parametric programming, Pages 222-235
· Chapter 18 - Bounded variable problems, Pages 236-244
· Chapter 19 - Transportation problems, Pages 245-274
· Chapter 20 - Assignment problems, Pages 275-290
· Chapter 21 - The decomposition principle for linear programs, Pages 291-
302
· Chapter 22 - Polynomial time algorithms for linear programming, Pages
303-320
· Chapter 23 - Nonlinear programming, Pages 323-339
· Chapter 24 - Quadratic programming, Pages 340-365

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