[R] constrained optimization help please!

[hayduke]

Hi All, 
I am having some real difficulty in trying to carry out constrained
optimization. I have had no problems with the Optim() function but when I
try to constrain the problem I am getting all sorts of error messages.
The model is a simple 2 area, 2 fleet, 1 stock model of a fishery. The code
is below. This code runs well but when I try the constrOptim() command with
an upper limit of f=6 for each fleet (total across 2 areas), the solver does
not run. 
Does anybody have any suggestions? Thanks.
nfleets<-2
nareas<-2
M<-1
M<-array(M,dim=c(nfleets,nareas))
N<-1000
cost<-c(40,40)
cost<-array(cost,dim=c(nfleets,nareas))
Price<-2
Price<-array(Price,dim=c(nfleets,nareas))
q<-array(0.1,dim=c(nfleets,nareas))
f<-1
f<-array(f,dim=c(nfleets,nareas))
init.eff<-array(3,dim=c(nfleets,nareas))
OF<-array(c(q*f), dim=c(nfleets, nareas))
Catch<-array(0,dim=c(nfleets, nareas))

obj<-function(f){
    f <- array(f, dim=c(nfleets, nareas))
    F <- q*f
    Z <- M+sum(F)
    S <- exp(-Z)
    Catch<- N*F/Z*(1-S)
    Tot.Catch <- sum(Catch)
    NR<-array(0,dim=c(nfleets,nareas))
    NR<-Price*Catch - f*cost
    d.NR<-array(0,dim=c(nfleets,nareas))
    f <- apply(f, 1, sum)
    d.NR<- N*q/Z*(1-S-F/Z+F/Z*S+F*S)*Price - cost 
    return(sum(d.NR*d.NR))
}

#zero.bnd <-  rep.int(0, length(f))
#opt.eff  <- optim( init.eff, obj, method="L-BFGS-B" )  

upper<-c(6,6)
lower<-c(0,0)

constropt.eff<-constrOptim(init.eff,obj,ui=upper, ci=lower,
method="Nelder-Mead")




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