Parallel coordinate plot (PCP)

Source: R/vis_pcp.R

Visualizes a Pareto-front approximation set with parallel coordinate plots. The \(x\)-axis shows the objectives as an ordered factor where the order is determined by the obj.cols argument. On the \(y\)-axis objective values are shown colored by solution as lines. Suitable for any number of objectives.

plot_pcp(df, obj.cols = c("y1", "y2"))

Arguments

df

[data.frame]
Data frame with columns at least those given via parameter obj.cols, “problem” and “algorithm”.
obj.cols

[character(>= 2)]
Column names of the objective function values. Default is c("y1", "y2").

Value

A ggplot object.

References

[1] T. Tušar and B. Filipič, Visualization of Pareto Front Approximations in Evolutionary Multiobjective Optimization: A Critical Review and the Prosection Method, in IEEE Transactions on Evolutionary Computation, vol. 19, no. 2, pp. 225-245, April 2015, doi: 10.1109/TEVC.2014.2313407.

See also

Other multi-objective visualizations: plot_eaf_diff(), plot_eaf(), plot_heatmap(), plot_radar(), plot_scatter2d(), plot_scatter3d()