Python Scipy Optimization Example: Constrained Box Volume
Ғылым және технология
This video shows how to perform a simple constrained optimization problem with scipy.minimize in Python. This video is part of an introductory series on optimization.
GEKKO Optimization Version: • Python Optimization Ex...
Пікірлер: 18
Thanks for taking a simple example to explain the optimise tool. Helped to quickly understand!
@beoptimistic5853
3 жыл бұрын
kzread.info/dash/bejne/ioR3yamNaaXSorQ.html 💐💐💐💐💐
Just what I needed, great video
@beoptimistic5853
3 жыл бұрын
kzread.info/dash/bejne/ioR3yamNaaXSorQ.html 💐💐💐💐💐
Hello, is it possible to have an output of a multi-objective function using Scipy? Thank you very much.
Good intro, thank you very much
@beoptimistic5853
3 жыл бұрын
kzread.info/dash/bejne/ioR3yamNaaXSorQ.html 💐💐💐💐💐
Thank you! What if you want to use more than one constraint?
@windguru22
4 жыл бұрын
same question here
This is a very similar problem I have but I have a linear obj func and constraint, and constraint is an equality. When using SLSQP I get error "singular matrix c in lsq subproblem". Seems I should use linprog but I'm not sure how or whether this type of problem can be converted to linprog. Any ideas?
thanks! very useful~ Can I ask what is difference between scipy.optimize and GEKKO?
@alphaopt2024
6 жыл бұрын
Good question. Scipy.optimize and GEKKO are two different options for doing optimization in Python. GEKKO is designed mainly for dynamic optimization, where a system is changing in time, but can also be used for steady state or design optimization where things are not changing with time. Both packages can be used with several different solvers. In my opinion GEKKO is easier to use, but scipy is more common.
@pkl520
6 жыл бұрын
Big thanks! Very clearly explain~~ hoping more video to come!
Thanks!
@beoptimistic5853
3 жыл бұрын
kzread.info/dash/bejne/ioR3yamNaaXSorQ.html 💐💐💐💐💐
very small font size... please consider using larger font size in future videos