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<DIV>Robin,</DIV>
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<DIV>This can vary substantially depending on the size and nonlinearity
structure of your problem, and your Matlab coding methods. The most important
information to look at is the timing results of “CPU secs in IPOPT” vs “CPU secs
in NLP function evaluations.” The former depends on the number of iterations,
algorithm options, and choice of linear system solver (Mumps vs MA57 etc) used
by Ipopt, and you won’t be able to improve it much by coding your problem in
C/C++. You can get more speedup in the NLP function evaluations, which is the
time spent evaluating the Matlab objective, gradient, constraint, Jacobian and
Hessian functions.</DIV>
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<DIV>You can get a more detailed breakdown of Ipopt timing by setting the option
print_timing_statistics to yes, and for the Matlab functions I highly recommend
using the Matlab profiler to identify time-consuming parts of your (or COBRA’s)
code.</DIV>
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<DIV>-Tony</DIV>
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