MATLAB: Interior-point algorithm vs SQP algoritm

fmincon

Hi, I am running an optimal design problem by using fmincon with sqp algorithm and interior-point algorithm. SQP algorithm was found the optimal and the exit message was (Local minimum found) while interior-point algorithm was given an exit flag (2) with exit message (Local minimum possible). So I used the optimum value which is given from SQP and re-run interior-point algorithm , but I still get tha same message (Local minimum possible). Why sqp was found the optimal wile interior-point algorithm did not? Thanks to all in advance.

Best Answer

Perhaps you are running into an inaccuracy due to using an interior-point method, or perhaps your problem has very high curvature or some other irregularity. It is hard to know based on the information you supplied.

Did you check the value that the interior-point algorithm gave? Was it unsatisfactory? Did you consult the documentation on Local Minimum Possible? It might give you some ideas about what is going on.

Good luck,

Alan Weiss

MATLAB mathematical toolbox documentation

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MATLAB: I have an array of data from a sensor which varies from positive to negative continuously. I want to find the peak value of each set of positive numbers and negative numbers.

>> findpeaks(X(X>0))
ans =
  Columns 1 through 10
    4.5190    4.5260    3.3360    3.1910    2.4630    1.8080    1.7910    1.3260    1.0030    0.7530
  Columns 11 through 20
    0.5650    0.4140    0.3060    0.3030    0.2290    0.2280    0.1710    0.1710    0.1300    0.1180
  Columns 21 through 30
    0.0980    0.0740    0.0520    0.0540    0.0410    0.0410    0.0320    0.0250    0.0190    0.0200
  Columns 31 through 40
    0.0020    0.0150    0.0150    0.0150    0.0110    0.0110    0.0110    0.0110    0.0070    0.0080
  Columns 41 through 50
    0.0090    0.0090    0.0090    0.0020    0.0040    0.0070    0.0020    0.0030    0.0030    0.0040
  Columns 51 through 59
    0.0050    0.0020    0.0020    0.0030    0.0030    0.0030    0.0030    0.0020    0.0020
>> abs(findpeaks(-X(X<0)))
ans =
  Columns 1 through 10
    3.8980    3.7790    2.8760    2.1120    2.1030    1.5570    1.5540    1.1540    0.8550    0.6340
  Columns 11 through 20
    0.4610    0.4700    0.3490    0.2600    0.1950    0.1450    0.1090    0.0790    0.0810    0.0590
  Columns 21 through 30
    0.0600    0.0600    0.0450    0.0450    0.0340    0.0270    0.0270    0.0200    0.0150    0.0150
  Columns 31 through 40
    0.0150    0.0100    0.0030    0.0100    0.0100    0.0100    0.0020    0.0060    0.0060    0.0060
  Columns 41 through 50
    0.0060    0.0050    0.0040    0.0020    0.0040    0.0040    0.0040    0.0040    0.0020    0.0020
  Columns 51 through 60
    0.0020    0.0020    0.0030    0.0030    0.0020    0.0020    0.0020    0.0020    0.0020    0.0020
  Columns 61 through 64
    0.0020    0.0020    0.0020    0.0020
>>

findpeaks is in Signal Processing Toolbox...

MATLAB: The objective function is increased rather than decreased when fmincon is used

You must not only look at the "f(x)"-column, but also at the "feasibility" column.

What is a "solution" good for if it is not feasible ?

Best wishes

Torsten.

Best Answer

Related Solutions

MATLAB: I have an array of data from a sensor which varies from positive to negative continuously. I want to find the peak value of each set of positive numbers and negative numbers.

MATLAB: The objective function is increased rather than decreased when fmincon is used

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