compute_R2HV: Modified powered tchebyscheff R2-indicator designed to...
In MaOEA: Many Objective Evolutionary Algorithm

Description Usage Arguments Value References Examples

Compute the R2-HV from Shang et al.

1	compute_R2HV(dataPoints, reference, weights = NULL, nPoints = 100)

`dataPoints`	The Points coordinate. Each column contains a single point (column major).
`reference`	The reference point for computing R2-mtch (similar as reference for HV)
`weights`	The weights/direction to be used to compute the achievement scalarization. Each column contains a single weight vector. If no weight is supplied, weights are generated using Sobol sequences.
`nPoints`	Used only when no weights are supplied. An input for the weight generator (sobol sequences). This defines how many points are created.

The function return the powered R2-indicator of the set.

Ke Shang, Hisao Ishibuchi, Min-Ling Zhang, and Yiping Liu. 2018. A new R2 indicator for better hypervolume approximation. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '18), Hernan Aguirre (Ed.). ACM, New York, NY, USA, 745-752. DOI: https://doi.org/10.1145/3205455.3205543

nPointToSample <- 100
nObjective <- 3
points <- matrix(runif(nPointToSample*nObjective), nrow = nObjective) # sample the points
ranks <- nsga2R::fastNonDominatedSorting(t(points)) # non-dominated sorting
points <- points[,ranks[[1]],drop=FALSE] # take only the non-dominated front
nPoints <- ncol(points) # check how many points are on the non-dominated front
reference <- rep(2,nObjective)

compute_R2HV(points,reference)