SACOBRA (version 1.2)

startCobra: Start COBRA (constraint-based optimization) phase I and/or phase II

Description

Start COBRA (constraint-based optimization) phase I and/or phase II for object cobra

Usage

startCobra(cobra)

Arguments

cobra

initialized COBRA object, i.e. the return value from cobraInit

Value

cobra, an object of class COBRA

See Also

cobraInit, cobraPhaseI, cobraPhaseII

Examples

# NOT RUN {
## solve G01 problem

## defining the constraint problem: G01
fn<-function(x){
   obj<- sum(5*x[1:4])-(5*sum(x[1:4]*x[1:4]))-(sum(x[5:13]))
   g1<- (2*x[1]+2*x[2]+x[10]+x[11] - 10)
   g2<- (2*x[1]+2*x[3]+x[10]+x[12] - 10)
   g3<- (2*x[2]+2*x[3]+x[11]+x[12] - 10)

   g4<- -8*x[1]+x[10]
   g5<- -8*x[2]+x[11]
   g6<- -8*x[3]+x[12]

   g7<- -2*x[4]-x[5]+x[10]
   g8<- -2*x[6]-x[7]+x[11]
   g9<- -2*x[8]-x[9]+x[12]

   res<-c(obj, g1 ,g2 , g3 
         , g4 , g5 , g6 
         , g7 , g8 , g9)
   return(res)
}
fName="G01"
d=13
lower=rep(0,d)
upper=c(rep(1,9),rep(100,3),1)
set.seed(1)
xStart<-runif(d,min=lower,max=upper)

## Initializing cobra
cobra <- cobraInit(xStart=xStart, fn=fn, fName=fName, lower=lower, upper=upper, 
                   feval=55, seqFeval=400, initDesPoints=3*d, DOSAC=1, cobraSeed=1)
                    
cobra <- startCobra(cobra)
## The true solution is at solu = c(rep(1,9),rep(3,3),1)
## where the optimum is f(solu) = optim = -15
## The solutions from SACOBRA is close to this:
print(getXbest(cobra))
print(getFbest(cobra))

## Plot the resulting error (best-so-far feasible optimizer result - true optimum)
## on a logarithmic scale:
optim = -15
plot(cobra$df$Best-optim,log="y",type="l",ylab="error",xlab="iteration",main=fName)
                            
# }