 # Multi-response optimization with 3 variables

I would like to find the optimal solution for y1, y2, and y3 as responses to x1, x2 and x3 (-1 <= x1 <= +1, -1 <= x2 <= +1, -1 <= x3 <= +1).

y1 and y3 are aimed to be maximized while y2 is to be minimized.

``````f <- function(x){
y1 <- 1137.2800 + 1.7625*x - 6.5625*x + 2.8250*x +
10.5000*x*x + 2.7250*x*x - 12.8250*x*x - 19.0400*x^2 -
28.0900*x^2 - 6.5150*x^2

y2 <- 3.0379534 + 0.0058166*x - 0.0250000*x +
0.1169284*x + 0.0945590*x*x + 0.0194053*x*x - 0.1932280*x*x -
0.1812333*x^2 - 0.1127556*x^2 - 0.2191618*x^2

y3 <- 5.84558 + 0.93671*x - 1.01269*x + 0.44442*x +
0.20850*x*x + 0.65710*x*x - 0.35850*x*x - 0.54678*x^2 -
1.16211*x^2 - 0.52700*x^2

y <- y1 - y2 + y3
}
``````

It would be great if sbd could help me find the optimal solution which yields maximum of y1 and y3 and minimum of y2 simultaneously using optim, optim_nm, and desirability package.

Thank you!

What problem have you found when trying to do this ?
You are more likely to receive assistance if you share code that requires improvement as opposed to asking others to do work from the first step to the last. (forum advice)

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