Optimization Theory Book

I	Continuous optimization	1
1	Optimality criteria on simple regions	3
2	Constraints, Lagrange function, optimality	19
3	Parametric aspects, semi-infinite optimization	35
4	Convex functions, duality, separation theorem	49
5	Linear inequalities, constraint qualifications	67
6	Linear programming : the simplex method	81
7	The ellipsoid method	97
8	Karmarkar's method for linear programming	113
9	Order of convergence, steepest descent	125
10	Conjugate direction, variable metric	141
11	Penalty-, barrier-, multiplier-, IP-methods	153
12	Search methods without derivatives	173
13	One-dimensional minimization	183
II	Discrete optimization	191
14	Graphs and networks	193
15	Flows in networks	227
16	Applications of the max-flow min-cut theorem	239
17	Integer linear programming	257
18	Computability; the Turing machine	271
19	Complexity theory	283
20	Reducibility and NP-completeness	301
21	Some NP-completeness results	313
22	The random access machine	329
23	Complexity theory over the real numbers	333
24	Approximating NP-hard problems	353
25	Approximation algorithms for TSP	365
26	Approximation algorithms for bin packing	375
27	A FPTAS for knapsack	383
28	Miscellaneous	391