hello ,i m quite new to Matlab and im sorry if my question is too trivial but i couldnt find answers in help.Im trying to solve an optimisation problem .given the execution time for different tasks(sorting algorithms),i plotted the cumulative distribution functions.(y axis-cumulative probability Q ;x axis-execution time t)(adsbygoogle = window.adsbygoogle || []).push({});

I've managed to reduce my problem to this ;where NORMINV(Q,mu,sigma)=inverse of the normal cumulative distribution with mean 'mu',stddev 'sigma'

Is it possible to solve such a problem in Matlab?i just want to confirm or how i can make it mathlab compatible.

my problem is having derivatives in the constraints function.

maximize Q

s.t

n

Sum (NORMINV(Q,mu_i ,sigma_i ) * k_i ) <= K

i=0

where k_i,K ,n are known constants.

thank you

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# Matlab optimisation problems

Can you offer guidance or do you also need help?

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