20k views

### Optimization when Cost Function Slow to Evaluate

Gradient descent and many other methods are useful for finding local minima in cost functions. They can be efficient when the cost function can be evaluated quickly at each point, whether numerically ...
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1 vote
4k views

• 2,688
1 vote
893 views

### How to use Design of Experiment (DoE) to reduce the number of simulations?

I am planning to do simulation for parametric study and there are 9 parameters in total. I was suggested to use DoE to reduce the number of simulations that I need to do. I studied the basic of DoE ...
1 vote
867 views

### Select optimal points for Gaussian process with a well-known target function

I'm currently trying to select the optimal points for a Gaussian Process Regression, and the important thing is that i already know the whole target function. Therefore, it's not Online Learning ...
• 399
1 vote
736 views

### How do I choose which design of experiments method to use?

I'm setting up a computer simulation (which I know changes the design of experiments methods) and I can't really determine how to choose which design of experiments (DOE) method to use. I'm a little ...
• 367
108 views

### Why are global search algorithms not used in DoE?

I'm reading about Design of Experiments via various textbooks (e.g. Montgomery's), and powerful global optimization methods (such as Ant Colony Optimization) are not used. They rely only on a basic ...
1 vote
175 views

### Space filling vs D,A,I,etc-optimal experiment design [closed]

What are some of the criteria for choosing one family over the other of experiment design methods ? How does this choice relate to the model of the response ? I left factorial / fractional factorial ...
• 141
1 vote
70 views

### Sampling plan for surrogate modelling

I am trying to develop a surrogate model for a thermoacoustic engine. The engine is modelled in a program called DeltaEC. I have developed automation code so that I can change parameters, run the ...
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81 views

### Is there a good framework for using Active Learning (reinforcement learning?) for Experimental Design?

We have a frequent problem that we deal with in a research environment that essentially boils down to finding the optimum conditions in a certain experimental space. At the moment we essentially solve ...
1 vote
37 views

### DoE for optimization / control approach?

I'm wondering whether a DoE approach could somehow be used as kind of an optimization algorithm? One of my current tasks is to find a set of five parameter which max a sixth one (see here for more: ...
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