PartRace: Race to solve the partition problem

In arnaud-m/partition: Race to Solve the Partition Problem

Description

Set up, execute, and log a race between several solvers (candidates) to solve partition problem's instances (task). It requires the package race.

Usage

PartRace(candidates, tasks, maxExp = 0, stat.test = c("friedman",
  "t.bonferroni", "t.holm", "t.none"), conf.level = 0.95, first.test = 10,
  interactive = TRUE, log.file = "", timeout = NA, plot.file = "")

Arguments

candidates	a character vector which contains the names of the solver's functions
tasks	a list of integer sets (numeric vector)
maxExp	Maximum number of experiments (i.e. evaluations of the function race.wrapper) that are allowed before selecting the best candidate. If maxExp=0, no limit is imposed... very unrealistic in practice.
stat.test	Statistical test to be used for discarding inferior candidates.
conf.level	The confidence level to be used for the statistical test.
first.test	The first test for discarding inferior candidates is performed only when all candidates have been evaluated on a minimum number of tasks equal to first.test.
interactive	If TRUE, print a progress report on the standard output.
log.file	File for saving periodically the state of the race.
timeout	per run in seconds (one candidate executes one task) that requires the package R.utils
plot.file	filename to plot the progress of the race.

See Also

race, race.wrapper,

Examples

## Generate five random instances of the partition problem
tasks <- PartGenInt( m = 5)
## Functions that return a random partition 
BeatMe <- function(sizes) sample(c(TRUE,FALSE),length(sizes), replace=TRUE)
BeatMeAgain <- BeatMe
## vector of candidate names
candidates <- c("BeatMe", "BeatMeAgain")
## Race between the two functions/algorithms
PartRace(candidates, tasks, plot.file = NA)

arnaud-m/partition documentation built on May 10, 2019, 1:44 p.m.