Timeline for What are the advantages/disadvantages of design of experiments (DoE) versus stochastic optimization methods
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| Jun 29, 2021 at 15:00 | history | tweeted | twitter.com/StackStats/status/1409889423165112333 | ||
| Jun 29, 2021 at 0:48 | answer | added | 4.Pi.n | timeline score: 1 | |
| Jun 28, 2021 at 9:40 | comment | added | Tianxun Zhou | Hi @mkt, let's say I am using genetic algorithm, I will generate a random set of initial starting points in the entire search space and evaluate the outcomes of each through the experiments. After which, the k-best performing points goes through "reproduction" to produce offspring candidate points by taking some linear combinations of their values. The poor performing points are eliminated. Some new points are also generated randomly, and in the next iteration, all of these points are evaluated and this process goes on for n number of iterations until convergence. | |
| Jun 28, 2021 at 9:33 | comment | added | mkt | I'm not too familiar with either approach, but I have some idea about how DoE works. Could you elaborate on how the stochastic optimization methods work to assist with experimental design? | |
| Jun 28, 2021 at 9:19 | history | edited | Tianxun Zhou | CC BY-SA 4.0 |
added 28 characters in body
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| Jun 28, 2021 at 2:53 | history | asked | Tianxun Zhou | CC BY-SA 4.0 |