Various strategies of Two-Phase Local Search applied to the Permutation Flowshop Problem with Makespan and Weighted Tardiness objectives.

Usage

tpls50x20_1_MWT

Format

A data frame with 1511 observations of 4 variables:

algorithm: TPLS search strategy
Makespan: first objective values.
WeightedTardiness: second objective values.
run: index of the run.

Source

Jérémie Dubois-Lacoste, Manuel López-Ibáñez, Thomas Stützle (2011). “Improving the Anytime Behavior of Two-Phase Local Search.” Annals of Mathematics and Artificial Intelligence, 61(2), 125–154. doi:10.1007/s10472-011-9235-0 .

Examples

data(tpls50x20_1_MWT)
str(tpls50x20_1_MWT)
#> 'data.frame':	1511 obs. of  4 variables:
#>  $ algorithm        : chr  "1to2" "1to2" "1to2" "1to2" ...
#>  $ Makespan         : num  4280 4238 4137 4024 4014 ...
#>  $ WeightedTardiness: num  10231 10999 11737 14871 17825 ...
#>  $ run              : num  1 1 1 1 1 1 1 1 1 1 ...