pga<-function(y, X, m, N, B=100, mutation=1/ncol(X), 
  start=NULL, prior = 0.3, ...)
{
# performs parallel genetic algorithm for variable selection
# by Mu Zhu
# first version = Jan 2002
# this version  = Feb 2009
#
# Inputs:
# m        = population size, default set to roughly ncol(X)
# N        = number of generations per path
# B        = number of parallel paths
# mutation = mutation rate, default set to roughly 1/m
# start    = starting population, pretty much useless
# prior    = controls the density of 1's in the initial population
#
# Feb09 addition:
# the use of 'shuffle' before and after calling sga 

  b <- 0; p <- ncol(X)
  rslt <- matrix(0, B, p)
  cat("Starting PGA...\n")
  while (b < B)
  {
    print(b)
    b <- b + 1    
    shuffle=sample(1:ncol(X))
    tmp <- sga(y, X[,shuffle], m, N, start, mutation, prior)
    rslt[b,] <- tmp$combo.gene[order(shuffle)]
  }
  return(rslt)
}