Package org.moeaframework.algorithm


package org.moeaframework.algorithm
Implementations of various algorithms and support tools for working with algorithms.
  • Class
    Description
    Abstract class providing default implementations for several Algorithm methods.
    Abstract class providing default implementations for several EvolutionaryAlgorithm methods.
    Implementation of AGE-MOEA-II, which is an adaptive evolutionary algorithm that estimates the Pareto front geometry and uses this to score solutions during selection.
    An exception that originated from an algorithm.
    An exception that originated from an algorithm during initialization.
    An exception that originated from an algorithm during termination.
    Deprecated.
    Use CheckpointExtension instead
    The Covariance Matrix Adaption Evolution Strategy (CMA-ES) algorithm for single and multi-objective problems.
    Implementation of the Improved Decomposition-Based Evolutionary Algorithm (I-DBEA).
    A provider of default algorithms.
    Implementation of the ε-MOEA algorithm.
    Implements the ε-NSGA-II algorithm.
    Implementation of the Generalized Differential Evolution (GDE3) algorithm.
    Implementation of the Indicator-Based Evolutionary Algorithm (IBEA).
    Implementation of MOEA/D, the multiobjective evolutionary algorithm with decomposition.
    Implementation of the Multiple Single Objective Pareto Sampling (MSOPS) algorithm.
    Population implementing the ranking scheme used by the Multiple Single Objective Pareto Sampling (MSOPS) algorithm.
    Implementation of NSGA-II, with the ability to attach an optional ε-dominance archive.
    Implementation of NSGA-III.
    Implementation of the (1+1) Pareto Archived Evolution Strategy (PAES).
    Implementation of the Pareto Envelope-based Selection Algorithm (PESA2).
    Random search implementation.
    Implementation of the reference-point-based nondominated sorting method for NSGA-III.
    A reference vector guided population, for use with RVEA, that truncates the population using the method outlined in [1].
    Implementation of the Reference Vector Guided Evolutionary Algorithm (RVEA).
    Implementation of the S-metric Selection MOEA (SMS-MOEA).
    Implementation of the strength-based evolutionary algorithm (SPEA2).
    Mapping of pair-wise distances between points.
    Implementation of the "unified" NSGA-III, or U-NSGA-III, which improves selection pressure by replacing the random selection of NSGA-III with tournament selection.
    Implementation of the Vector Evaluated Genetic Algorithm (VEGA).