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On 01/23/2014 07:23 PM, Tobias Schmidt wrote:
>> OK, in my understanding the optimization should be executable
>> with a gradient-based algorithm if I set *grad* to a constant
>> value instead of a calculated one. A short try also fails with
>> the nlopt roundoff- limited exception after the first
>> optimization step.
> 
> I found out that the constant value, which I previously set as 
> "gradient" was too small. A bigger one causes the program to run 
> successfully! Hence, it led me implementing the gradient
> calculations based on the difference quotients.
> 
> Unfortunately, the optimization converges with an x vector which 
> violates the constraints, but the "last_optimize_result()" says 
> "FTOL_REACHED"! Does either the way I define or add the functions
> cause the violations?

Firstly: Try a smaller value for the quotient of your difference
quotient, d.

Secondly: SQP is a local method, and hence, will only find a
stationary point of the constraint optimization problem. If either
your objective function or our constraints are not convex, this can
very well  violate the constraints (if you, locally, cannot improve
any constraint without making another one worse).

Is your solution "close" to the matlab solution? If yes, you probably
have numerical problems with your gradient approximation. If no, you
could be stuck in a local stationary point.

Best,
Julius

> Regards, Tobias
> 
> 
> _______________________________________________ NLopt-discuss
> mailing list [email protected] 
> http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
> 


- -- 
Dipl.-Inform. Julius Ziegler <[email protected]>

Institut für Mess- und Regelungstechnik
Karlsruher Institut für Technologie

Department of Measurement and Control
Karlsruhe Institute of Technology

Engler-Bunte-Ring 21
76131 Karlsruhe

Tel. +49 721 608 47146

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