sqp method - slow

1 回表示 (過去 30 日間)
LuC
LuC 2016 年 7 月 12 日
編集済み: LuC 2016 年 7 月 12 日
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)

回答 (0 件)

カテゴリ

Help Center および File ExchangeSolver Outputs and Iterative Display についてさらに検索

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by