Run-length distribution (RLD) Analysis of Algorithm Instances
|Reported by:||abeham||Owned by:||abeham|
Run-length distributions give insight into the required algorithmic effort (in terms of function evaluations or wall-clock time) for reaching a certain target.
The empirical cumulative distribution function (ECDF) 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 distribution.
RLD Analysis is to be included through analyzer operators that can be attached to the Analyzers of an algorithm instance. When run they track the monotonic convergence graph. In addition a run collection view is to be created that constructs and displays the ECDF.
Change History (9)
comment:3 Changed 9 months ago by abeham
- Component changed from Analysis.Views to Analysis
- Owner changed from abeham to mkommend
- Status changed from accepted to reviewing
comment:4 Changed 9 months ago by mkommend
- Milestone changed from HeuristicLab 3.3.14 to HeuristicLab 3.3.15
comment:5 Changed 7 months ago by mkommend
- Owner changed from mkommend to abeham
- Status changed from reviewing to assigned