Maybe you can try fmincon from package pracma like below
pracma::fmincon(c(0,0,0,0),
f,
gr = grad,
Aeq = cbind(1,1,1,1),
beq = 1,
lb = c(0,0,0,0),
ub = c(1,1,1,1))
I want to minimize function
f <- function(u){
return(-(1+u[1]+u[2]+u[3]+u[4]))
}
with gradient grad
And I have constraints:
1) u[1]+u[2]+u[3]+u[4] = 1
2) 0<=u[1]<=1, 0<=u[2]<=1, 0<=u[3]<=1, 0<=u[4]<=1
How to make it correctly? I can make it only for 2 constraint
optim(par=c(0,0,0,0), fn=f,lower=c(0, 0, 0, 0), upper=c(1, 1, 1, 1),method="L-BFGS-B")
But 1 constraint is not true in this case
Maybe you can try fmincon from package pracma like below
pracma::fmincon(c(0,0,0,0),
f,
gr = grad,
Aeq = cbind(1,1,1,1),
beq = 1,
lb = c(0,0,0,0),
ub = c(1,1,1,1))
It seems like true solution but i have
Argument 'Aeq' must be a matrix with length(x0) columns. Thoughlength(x0) = length(Aeq) = 4Got it.
Aeq = cbind(1,1,1,1)@ИльшатМурзурбеков Great that you fixed it. Does this address your question?