Package index • moocore

Pareto dominance

is_nondominated() filter_dominated() pareto_rank(): Identify, remove and rank dominated points according to Pareto optimality

Multi-objective performance assessment metrics

epsilon_additive() epsilon_mult(): Epsilon metric

hv_contributions(): Hypervolume contribution of a set of points

hypervolume(): Hypervolume metric

igd() igd_plus() avg_hausdorff_dist(): Inverted Generational Distance (IGD and IGD+) and Averaged Hausdorff Distance

whv_hype(): Approximation of the (weighted) hypervolume by Monte-Carlo sampling (2D only)

whv_rect() total_whv_rect(): Compute (total) weighted hypervolume given a set of rectangles

Computing the Empirical Attainment Function

vorobT() vorobDev(): Vorob'ev computations

attsurf2df(): Convert a list of attainment surfaces to a single EAF data.frame.

choose_eafdiff(): Interactively choose according to empirical attainment function differences

compute_eaf_call(): Same as eaf() but performs no checks and does not transform the input or the output. This function should be used by other packages that want to avoid redundant checks and transformations.

compute_eafdiff_call(): Same as eafdiff() but performs no checks and does not transform the input or the output. This function should be used by other packages that want to avoid redundant checks and transformations.

eaf(): Exact computation of the EAF in 2D or 3D

eaf_as_list(): Convert an EAF data frame to a list of data frames, where each element of the list is one attainment surface. The function attsurf2df() can be used to convert the list into a single data frame.

eafdiff(): Compute empirical attainment function differences

largest_eafdiff(): Identify largest EAF differences

Read/Write/Transform datasets

read_datasets(): Read several data sets

write_datasets(): Write data sets

normalise(): Normalise points

rbind_datasets(): Combine datasets x and y by row taking care of making all sets unique.

transform_maximise(): Transform matrix according to maximise parameter

as_double_matrix(): Convert input to a matrix with "double" storage mode (base::storage.mode()).

Datasets

CPFs: Conditional Pareto fronts obtained from Gaussian processes simulations.

HybridGA: Results of Hybrid GA on Vanzyl and Richmond water networks

SPEA2minstoptimeRichmond: Results of SPEA2 when minimising electrical cost and maximising the minimum idle time of pumps on Richmond water network.

SPEA2relativeRichmond: Results of SPEA2 with relative time-controlled triggers on Richmond water network.

SPEA2relativeVanzyl: Results of SPEA2 with relative time-controlled triggers on Vanzyl's water network.

tpls50x20_1_MWT: Various strategies of Two-Phase Local Search applied to the Permutation Flowshop Problem with Makespan and Weighted Tardiness objectives.