Expand description
Performance indicators for multi-objective optimization
Provides metrics to evaluate the quality of Pareto fronts:
- Hypervolume (exact 2D sweep, Monte Carlo for higher dimensions)
- Inverted Generational Distance (IGD)
- Generational Distance (GD)
- Additive epsilon indicator
- Spread / diversity indicator
- Domination utilities and non-dominated sorting
§References
- Zitzler, Thiele (1998). Multiobjective Optimization Using Evolutionary Algorithms — A Comparative Case Study.
- Deb et al. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II.
- Van Veldhuizen & Lamont (1998). Evolutionary Computation and Convergence to a Pareto Front.
Enums§
- R2Utility
- Scalarizing utility function type for the R2 indicator.
Functions§
- additive_
epsilon_ indicator - Additive epsilon indicator (I_ε+).
- delta_
metric - Delta metric (Δ) — Deb’s modified spread measure.
- dominates
- Returns
trueif vectoraPareto-dominates vectorb. - generational_
distance - Generational Distance (GD).
- hypervolume_
2d - Exact 2-D hypervolume indicator.
- hypervolume_
contribution - Hypervolume contribution of each point in a Pareto front.
- hypervolume_
mc - Monte-Carlo hypervolume approximation for arbitrary number of objectives.
- igd
- Inverted Generational Distance (IGD).
- igd_
plus - Inverted Generational Distance Plus (IGD+).
- non_
dominated_ sort - Fast non-dominated sorting.
- r2_
indicator - R2 quality indicator.
- spacing_
metric - Spacing metric (SP).
- spread
- Spread / diversity indicator (Δ, Delta).