Problem definition and ranking#
Problem brings the objective function, objective directions, SearchSpace, and constraints together as one optimization target.
Constraint handling computes candidate feasibility and violations, and Comparator compares those results with objective values.
For multiple objectives, Dominator defines dominance and NonDominatedSorter builds layers of non-dominated solutions from that relation.
Decomposition scalarizes multiple objectives to enable decomposition-based comparison.
Defines the objective function, variables, objective directions, constraints, and SearchSpace.
Defines candidate representation and the services needed for sampling and validation.
Replaces violation aggregation, feasibility checks, and repair.
Ranks solutions from objective values and constraint violations.
Defines dominance relations between solutions, such as Pareto and ε-dominance.
Splits a population into non-dominated fronts using the dominance relation.
Provides decomposition functions that scalarize multiple objectives.