sqp method - slow
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Hi,
I run the sqp, active-set and interior-point methods on the same set of data and their options are the same. I am confused why it takes 20 minutes for sqp to find the solution while for the other two methods it takes less than 5 seconds.
My goal function is:
Err = sum((F_observed - F_raw) .^2);
Here is the 'iter' output:
Norm of First-order
Iter F-count f(x) Feasibility Steplength step optimality
0 16 2.027691e+05 0.000e+00 2.611e+06
1 55 2.015284e+05 0.000e+00 2.737e-04 8.211e-03 7.520e+06
2 88 1.915127e+05 0.000e+00 2.326e-03 6.598e-02 2.434e+06
3 122 1.892994e+05 0.000e+00 1.628e-03 4.342e-02 1.879e+06
4 160 1.876097e+05 0.000e+00 3.910e-04 1.067e-02 4.279e+06
5 189 1.785387e+05 0.000e+00 9.689e-03 2.448e-01 5.118e+06
6 218 1.612519e+05 0.000e+00 9.689e-03 2.418e-01 3.995e+06
7 244 1.543721e+05 0.000e+00 2.825e-02 6.225e-01 3.297e+06
8 271 1.370354e+05 0.000e+00 1.977e-02 4.613e-01 3.018e+06
9 295 1.306121e+05 1.000e+00 5.765e-02 1.114e+00 4.053e+06
10 324 1.243357e+05 1.000e+00 9.689e-03 2.222e-01 2.623e+06
11 348 1.210242e+05 1.000e+00 5.765e-02 1.063e+00 4.090e+06
12 372 1.083141e+05 0.000e+00 5.765e-02 1.042e+00 2.634e+06
13 393 1.041635e+05 0.000e+00 1.681e-01 1.947e+00 3.196e+06
14 417 8.626112e+04 1.000e+00 5.765e-02 8.158e-01 1.418e+06
15 438 8.510665e+04 0.000e+00 1.681e-01 1.190e+00 2.006e+06
16 455 7.392513e+04 0.000e+00 7.000e-01 3.826e+00 1.067e+06
17 471 6.790133e+04 0.000e+00 1.000e+00 1.544e+00 3.717e+05
18 496 6.783769e+04 0.000e+00 4.035e-02 8.082e-01 3.947e+05
19 512 6.718949e+04 0.000e+00 1.000e+00 8.408e-01 7.938e+04
20 528 6.704678e+04 0.000e+00 1.000e+00 1.287e-01 3.632e+04
21 544 6.701860e+04 0.000e+00 1.000e+00 2.931e-02 2.684e+04
22 560 6.700750e+04 0.000e+00 1.000e+00 5.487e-02 2.600e+04
23 576 6.700702e+04 0.000e+00 1.000e+00 2.736e-03 1.835e+03
24 592 6.700700e+04 0.000e+00 1.000e+00 1.416e-03 1.034e+03
25 608 6.700700e+04 0.000e+00 1.000e+00 2.349e-04 3.498e+01
26 624 6.700700e+04 0.000e+00 1.000e+00 2.100e-05 6.189e+00
27 640 6.700700e+04 0.000e+00 1.000e+00 6.972e-06 1.251e+00
28 641 6.700700e+04 0.000e+00 7.000e-01 8.553e-07 4.189e-01
Optimization completed: The relative first-order optimality measure, 6.074215e-07,
is less than options.TolFun = 1.000000e-06, and the relative maximum constraint
violation, 0.000000e+00, is less than options.TolCon = 1.000000e-06.
Optimization Metric Options
relative first-order optimality = 6.07e-07 TolFun = 1e-06 (selected)
relative max(constraint violation) = 0.00e+00 TolCon = 1e-06 (selected)
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