Iterative Display
Types of Iterative Display
Iterative display gives you information about the progress of solvers during their runs.
There are two types of iterative display:
Global solver display
Local solver display
Both types appear at the command line, depending on global and local options.
Obtain local solver iterative display by setting the Display option in the
problem.options field to "iter" or
"iter-detailed" with optimoptions. For
more information, see Iterative Display.
Obtain global solver iterative display by setting the Display property in
the GlobalSearch or MultiStart object to "iter".
Global solvers set the default Display option of the local solver to
"off", unless the problem structure has a value for this
option. Global solvers do not override any setting you make for local
options.
Note
Setting the local solver Display option to anything other
than "off" can produce a great deal of output. The default
Display option created by
optimoptions(@ is
solver)"final".
Examine Types of Iterative Display
Run the example described
in Run the Solver using GlobalSearch with GlobalSearch iterative
display:
% Set the random stream to get exactly the same output % rng(14,"twister") gs = GlobalSearch(Display="iter"); opts = optimoptions(@fmincon,Algorithm="interior-point"); sixmin = @(x)(4*x(1)^2 - 2.1*x(1)^4 + x(1)^6/3 ... + x(1)*x(2) - 4*x(2)^2 + 4*x(2)^4); problem = createOptimProblem("fmincon",x0=[-1,2],... objective=sixmin,lb=[-3,-3],ub=[3,3],... options=opts); [xming,fming,flagg,outptg,manyminsg] = run(gs,problem);
Num Pts Best Current Threshold Local Local
Analyzed F-count f(x) Penalty Penalty f(x) exitflag Procedure
0 34 -1.032 -1.032 1 Initial Point
200 1240 -1.032 0 1 Stage 1 Local
300 1342 -1.032 15.67 -0.2963 Stage 2 Search
400 1442 -1.032 102.6 1.022 Stage 2 Search
500 1542 -1.032 4.02 0.2542 Stage 2 Search
506 1582 -1.032 0.08424 0.2542 -1.032 1 Stage 2 Local
512 1623 -1.032 -0.2141 0.08424 -0.2155 1 Stage 2 Local
600 1711 -1.032 97.04 -0.7218 Stage 2 Search
700 1811 -1.032 114.7 -0.4829 Stage 2 Search
800 1911 -1.032 287.4 0.3737 Stage 2 Search
900 2011 -1.032 2.339 0.8699 Stage 2 Search
905 2060 -1.032 0.5993 0.8699 -0.2155 1 Stage 2 Local
1000 2155 -1.032 25.61 -1.03 Stage 2 Search
GlobalSearch stopped because it analyzed all the trial points.
All 5 local solver runs converged with a positive local solver exit flag.Run the same example without GlobalSearch iterative
display, but with fmincon iterative display:
gs.Display = "final"; problem.options.Display = "iter"; [xming,fming,flagg,outptg,manyminsg] = run(gs,problem);
First-order Norm of
Iter F-count f(x) Feasibility optimality step
0 3 4.823333e+01 0.000e+00 1.088e+02
1 7 2.020476e+00 0.000e+00 2.176e+00 2.488e+00
2 10 6.525252e-01 0.000e+00 1.937e+00 1.886e+00
3 13 -8.776121e-01 0.000e+00 9.076e-01 8.539e-01
4 16 -9.121907e-01 0.000e+00 9.076e-01 1.655e-01
5 19 -1.009367e+00 0.000e+00 7.326e-01 8.558e-02
6 22 -1.030423e+00 0.000e+00 2.172e-01 6.670e-02
7 25 -1.031578e+00 0.000e+00 4.278e-02 1.444e-02
8 28 -1.031628e+00 0.000e+00 8.777e-03 2.306e-03
9 31 -1.031628e+00 0.000e+00 8.845e-05 2.750e-04
10 34 -1.031628e+00 0.000e+00 8.744e-07 1.352e-06
Local minimum found that satisfies the constraints.
Optimization completed because the objective function is non-decreasing in
feasible directions, to within the value of the optimality tolerance,
and constraints are satisfied to within the value of the constraint tolerance.
First-order Norm of
Iter F-count f(x) Feasibility optimality step
0 3 -4.399715e-01 0.000e+00 1.980e+00
1 9 -9.929469e-01 0.000e+00 1.230e+00 3.442e-01
2 15 -1.028480e+00 0.000e+00 3.291e-01 9.982e-02
3 18 -1.031263e+00 0.000e+00 6.726e-02 3.436e-02
4 21 -1.031627e+00 0.000e+00 8.806e-03 7.753e-03
5 24 -1.031628e+00 0.000e+00 1.433e-04 3.723e-04
6 27 -1.031628e+00 0.000e+00 2.492e-06 2.254e-05
7 30 -1.031628e+00 0.000e+00 8.744e-07 3.155e-07
Local minimum found that satisfies the constraints.
Optimization completed because the objective function is non-decreasing in
feasible directions, to within the value of the optimality tolerance,
and constraints are satisfied to within the value of the constraint tolerance.
First-order Norm of
Iter F-count f(x) Feasibility optimality step
0 3 -1.906111e-01 0.000e+00 8.356e-01
1 14 -2.146803e-01 0.000e+00 1.300e-01 5.455e-02
2 20 -2.151309e-01 0.000e+00 1.060e-01 6.160e-03
3 23 -2.150434e-01 0.000e+00 9.182e-02 1.143e-02
4 26 -2.154599e-01 0.000e+00 1.558e-02 5.912e-03
5 29 -2.154638e-01 0.000e+00 2.230e-04 6.503e-04
6 32 -2.154638e-01 0.000e+00 1.543e-04 1.133e-05
7 35 -2.154638e-01 0.000e+00 1.543e-06 6.249e-06
8 38 -2.154638e-01 0.000e+00 2.600e-08 5.015e-08
Local minimum found that satisfies the constraints.
Optimization completed because the objective function is non-decreasing in
feasible directions, to within the value of the optimality tolerance,
and constraints are satisfied to within the value of the constraint tolerance.
GlobalSearch stopped because it analyzed all the trial points.
All 3 local solver runs converged with a positive local solver exit flag.Setting GlobalSearch iterative display, as
well as fmincon iterative display, yields both
displays intermingled.
For an example of iterative display in a parallel environment, see Parallel MultiStart.
