Optimizing over three variables

I have data sets from experiments where I alter three variables and measure the resulting efficiency of the system, given those conditions. Is there a way to take the data of some cases (the three variable parameters and the resulting efficiency) and optimize the efficiency over those three parameters. I am hoping to not need to take data for all combinations of the three variables but instead take a sweep of each one and use an optimization formula to get predictions of cobinations that would give maximum efficiency. I am unsure if this is something that can be done in Matlab or if machine learning would be needed.

Also, is there a good way to visualize the data in three dimensions to show which parameters result in the maximum effeciency?

Thank you!

Answer 1

[Shiva Kalyan Diwakaruni]

Hi,

Global Optimization Toolbox provides functions that search for global solutions to problems that contain multiple maxima or minima. Toolbox solvers include surrogate, pattern search, genetic algorithm, particle swarm, simulated annealing, multistart, and global search. You can use these solvers for optimization problems where the objective or constraint function is continuous, discontinuous, stochastic, does not possess derivatives, or includes simulations or black-box functions.

You can follow the below link for more information

https://www.mathworks.com/help/gads/index.html

thanks.