Particle swarm optimization

Interface to the particle swarm optimization (pso) algorithm.

Usage

pso(
  env,
  lb,
  ub,
  loss,
  ngen,
  npop,
  error_threshold,
  global = FALSE,
  saveSwarm = FALSE,
  runAsShiny = FALSE
)

Arguments

env

is something that is passed to the loss function in addition to the parameters which get optimized

lb

is a numeric vector defining the lower boundaries of the parameter

ub

is a numeric vector defining the upper boundaries of the parameter

loss

is the loss function for which the optimal parameter set should be found

ngen

is the number of generations the pso should run

npop

is the number of particles which should be used during optimization

error_threshold

is a number defining a sufficient small error at which the optimization is stopped

global

is a logical parameter. If set to TRUE a global star topology is used. Thus, each particle compares itself with the global best particle of the entire swarm. In contrast, if global is set to FALSE a random arbitrary neighborhood is used instead. Thus, each particle has a neighberhood which contains K neighbours where K is between 0 and 3. From the swarm K neighbours are drawn randomly. From the neighberhood the best particle is used for comparison. The neighberhood is calculated for each generation.

saveSwarm

is a logical value defining whether the entire optimization should be saved.

runAsShiny

is an internal parameter which is used when running the shiny app interface.

Examples

rosenbrock <- function(parameter, env, Ignore) {
 value <- 0
 for (i in 1:(length(parameter) - 1)) {
   value <- value + 
     100*(parameter[i + 1] - parameter[i]^2)^2 +
     (1 - parameter[i])^2
 }
return(value)
}

set.seed(1234)
res <- tsf::pso(new.env(), rep(-10, 3), rep(10, 3), rosenbrock, 1000, 40,
                 0.00001, TRUE, FALSE)
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