Algorithm performance comparison by ECDF

[abeham]

The empirical cumulative distribution function can be calculated from several runs of an optimization algorithm. From a first-hit graph several targets will be defined in the objective function and it will be measured when a target is hit by an algorithm. The proportion of all these hits forms the empirical cumulative distribution function (ECDF).

Necessary tasks:

1. Create analyzers that calculate the quality progress with respect to function evaluations and also with respect to wall-clock time
2. Create a run collection view that will calculate and compare the ECDF in one chart