BFGS Method
The problem:  Example6_1
iteration number:       1
s =
    0.4895   -0.2784
as =
         0    3.3693
fs =
    1.4041   -0.4291
x =
    2.1493   -0.4379
grad =
   -0.4833   -0.8506
gradient length squared:      0.9572
objective function value:     -0.4291
delx =
    1.6493
   -0.9379
Y =
    0.0062
   -1.1290
B =
    0.0000   -0.0066
   -0.0066    1.1922
C =
   -0.7556    0.4297
    0.4297   -0.2444
A =
    0.2444    0.4231
    0.4231    1.9478
iteration number:       2
s =
    1.9576    0.0114
as =
         0    3.3693    0.2720
fs =
    1.4041   -0.4291   -0.5564
x =
    2.6817   -0.4348
grad =
    0.0107   -1.7631
gradient length squared:      3.1088
objective function value:     -0.5564
delx =
    0.5324
    0.0031
Y =
    0.4940
   -0.9125
B =
    0.9381   -1.7327
   -1.7327    3.2004
C =
   -0.2444   -0.4301
   -0.4301   -0.7570
A =
    0.9381   -1.7396
   -1.7396    4.3912
iteration number:       3
s =
    2.7630    1.4961
as =
         0    3.3693    0.2720    0.3943
fs =
    1.4041   -0.4291   -0.5564   -1.4602
x =
    3.7710    0.1550
grad =
    0.9892   -1.8247
gradient length squared:      4.3079
objective function value:     -1.4602
delx =
    1.0894
    0.5899
Y =
    0.9784
   -0.0615
B =
    0.9299   -0.0585
   -0.0585    0.0037
C =
   -0.0000    0.0072
    0.0072   -1.1919
A =
    1.8679   -1.7909
   -1.7909    3.2030
iteration number:       4
s =
    0.0358    0.5897
as =
         0    3.3693    0.2720    0.3943    1.5450
fs =
    1.4041   -0.4291   -0.5564   -1.4602   -2.3206
x =
    3.8264    1.0661
grad =
    1.8648   -0.1121
gradient length squared:      3.4901
objective function value:     -2.3206
delx =
    0.0553
    0.9111
Y =
    0.8757
    1.7125
B =
    0.4766    0.9322
    0.9322    1.8231
C =
   -0.9403    1.7345
    1.7345   -3.1996
A =
    1.4043    0.8758
    0.8758    1.8265
iteration number:       5
s =
   -1.9492    0.9961
as =
         0    3.3693    0.2720    0.3943    1.5450    0.3503
fs =
    1.4041   -0.4291   -0.5564   -1.4602   -2.3206   -2.9974
x =
    3.1436    1.4150
grad =
    0.0514    0.0982
gradient length squared:      0.0123
objective function value:     -2.9974
delx =
   -0.6828
    0.3489
Y =
   -1.8134
    0.2104
B =
    2.5071   -0.2908
   -0.2908    0.0337
C =
   -0.9282    0.0558
    0.0558   -0.0034
A =
    2.9832    0.6408
    0.6408    1.8569
iteration number:       6
s =
   -0.0063   -0.0507
as =
         0    3.3693    0.2720    0.3943    1.5450    0.3503    0.9675
fs =
    1.4041   -0.4291   -0.5564   -1.4602   -2.3206   -2.9974   -3.0000
x =
    3.1374    1.3660
grad =
   -0.0102    0.0024
gradient length squared:    1.0884e-004
objective function value:     -3.0000
delx =
   -0.0061
   -0.0491
Y =
   -0.0616
   -0.0958
B =
    0.7462    1.1615
    1.1615    1.8079
C =
   -0.4980   -0.9515
   -0.9515   -1.8180
A =
    3.2314    0.8508
    0.8508    1.8467
iteration number:       7
s =
    0.0040   -0.0031
as =
         0    3.3693    0.2720    0.3943    1.5450    0.3503    0.9675    1.0140
fs =
    1.4041   -0.4291   -0.5564   -1.4602   -2.3206   -2.9974   -3.0000   -3.0000
x =
    3.1415    1.3628
grad =
  1.0e-003 *
    0.7657   -0.2267
gradient length squared:    6.3765e-007
objective function value:     -3.0000
The design vector,function value and KT value 
during the iterations
    0.5000    0.5000    1.4041         0    0.3171
    2.1493   -0.4379   -0.4291    3.3693    0.9572
    2.6817   -0.4348   -0.5564    0.2720    3.1088
    3.7710    0.1550   -1.4602    0.3943    4.3079
    3.8264    1.0661   -2.3206    1.5450    3.4901
    3.1436    1.4150   -2.9974    0.3503    0.0123
    3.1374    1.3660   -3.0000    0.9675    0.0001
    3.1415    1.3628   -3.0000    1.0140    0.0000
ans =
    3.1415    1.3628   -3.0000
