library(n1qn1)
library(lbfgs)
library(lbfgsb3)
library(GenSA)

Rastrigin <- function(x) {
  functionCalls <<- functionCalls + 1
  return(sum(x^2 - 10 * cos(2 * pi * x)) + 10 * length(x))
}

# call this to calculate gradient for each variable
# Rastrigin4d <- "~ w^2 - 10 * cos(2 * pi * w)  +  x^2 - 10 * cos(2 * pi * x)  +  y^2 - 10 * cos(2 * pi * y)  +  z^2 - 10 * cos(2 * pi * z)   +  10 * 4"
# deriv(formula(Rastrigin4d), c("w","x","y","z"))

Rastrigin4d_Grad <- function(w){
  functionCalls <<- functionCalls + 1
  z <- w[4]
  y <- w[3]
  x <- w[2]
  w <- w[1]
  return(c(
    2 * w + 10 * (sin(2 * pi * w) * 2 * pi),
    2 * x + 10 * (sin(2 * pi * x) * 2 * pi),
    2 * y + 10 * (sin(2 * pi * y) * 2 * pi),
    2 * z + 10 * (sin(2 * pi * z) * 2 * pi)
  ))
}


functionCalls <- 0
result1 <- n1qn1(call_eval = Rastrigin,
                 call_grad = Rastrigin4d_Grad,
                 max_iterations = .Machine$integer.max,
                 nsim = .Machine$integer.max,
                 vars = c(1000,1000,1000,1000))
cat("n1qn1 fitness function calls:", functionCalls, "; parameters =", result1$par, "; result =", Rastrigin(result1$par), "\n")



functionCalls <- 0
result2 <- lbfgs(call_eval = Rastrigin,
                 call_grad = Rastrigin4d_Grad,
                 vars = c(1000,1000,1000,1000),
                 invisible = TRUE)
cat("lbfgs fitness function calls:", functionCalls, "; parameters =", result2$par, "; result =", Rastrigin(result2$par), "\n")



functionCalls <- 0
result3 <- lbfgsb3(prm = c(1000,1000,1000,1000),
                   fn = Rastrigin,
                   gr = Rastrigin4d_Grad,
                   lower <- c(-1000,-1000,-1000,-1000),
                   upper <- c( 1000, 1000, 1000, 1000))
cat("lbfgsb3 fitness function calls:", functionCalls, "; parameters =", result3$prm, "; result =", Rastrigin(result3$par), "\n")



functionCalls <- 0
result4 <- GenSA(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 lower <- c(-1000,-1000,-1000,-1000),
                 upper <- c( 1000, 1000, 1000, 1000))
cat("GenSA fitness function calls:", functionCalls, "; parameters =", result4$par, "; result =", Rastrigin(result4$par), "\n")



functionCalls <- 0
result5 <- optim(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 method = "Nelder-Mead")
cat("optim Nelder-Mead fitness function calls:", functionCalls, "; parameters =", result5$par, "; result =", Rastrigin(result5$par), "\n")



functionCalls <- 0
result6 <- optim(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 method = "BFGS")
cat("optim BFGS fitness function calls:", functionCalls, "; parameters =", result6$par, "; result =", Rastrigin(result6$par), "\n")



functionCalls <- 0
result7 <- optim(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 method = "CG")
cat("optim CG fitness function calls:", functionCalls, "; parameters =", result7$par, "; result =", Rastrigin(result7$par), "\n")



functionCalls <- 0
result8 <- optim(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 method = "L-BFGS-B")
cat("optim L-BFGS-B fitness function calls:", functionCalls, "; parameters =", result8$par, "; result =", Rastrigin(result8$par), "\n")



functionCalls <- 0
result9 <- optim(par = c(1000,1000,1000,1000),
                 fn = Rastrigin,
                 method = "SANN")
cat("optim SANN fitness function calls:", functionCalls, "; parameters =", result9$par, "; result =", Rastrigin(result9$par), "\n")