Is it possible to use the R package utility to perform a decision analysis based on multiattribute utility theory (MAUT)? The package is seemingly for providing decision support, but the instructions lack any references to decision alternatives or performance matrices, that are essential elements in MCDA. Therefore, it remains unclear to me how exactly this package is meant to be used.

Below is an ordinary performance matrix of decision alternatives. Can you help me to find the best alternative with the MAUT approach using utility?

Performance matrix

structure(list(g1 = c(18342L, 15335L, 16973L, 15460L, 15131L, 
13841L, 18971L, 18319L, 19800L, 17537L, 15980L, 17219L, 21334L
), g2 = c(30.7, 30.2, 29, 30.4, 29.7, 30.8, 28, 28.9, 29.4, 28.3, 
29.6, 30.2, 28.9), g3 = c(37.2, 41.6, 34.9, 35.8, 35.6, 36.5, 
35.6, 35.3, 34.7, 34.8, 35.3, 36.9, 36.7), g4 = c(2.33, 2, 2.66, 
1.66, 1.66, 1.33, 2.33, 1.66, 2, 2.33, 2.33, 1.66, 2), g5 = c(3, 
2.5, 2.5, 1.5, 1.75, 2, 2, 2, 1.75, 2.75, 2.75, 1.25, 2.25)), class = "data.frame", row.names = c("a01", 
"a02", "a03", "a04", "a05", "a06", "a07", "a08", "a09", "a11", 
"a12", "a13", "a14"))