tpls50x20_1_MWT {moocore}

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

Description

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.

set

indices of corresponding conditional Pareto fronts.

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)