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[1] - 6.5625*x[2] + 2.8250*x[3] +
10.5000*x[1]*x[2] + 2.7250*x[1]*x[3] - 12.8250*x[2]*x[3] - 19.0400*x[1]^2 -
28.0900*x[2]^2 - 6.5150*x[3]^2
y2 <- 3.0379534 + 0.0058166*x[1] - 0.0250000*x[2] +
0.1169284*x[3] + 0.0945590*x[1]*x[2] + 0.0194053*x[1]*x[3] - 0.1932280*x[2]*x[3] -
0.1812333*x[1]^2 - 0.1127556*x[2]^2 - 0.2191618*x[3]^2
y3 <- 5.84558 + 0.93671*x[1] - 1.01269*x[2] + 0.44442*x[3] +
0.20850*x[1]*x[2] + 0.65710*x[1]*x[3] - 0.35850*x[2]*x[3] - 0.54678*x[1]^2 -
1.16211*x[2]^2 - 0.52700*x[3]^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!