Package org.uma.jmetal.component.examples.multiobjective.nsgaii
package org.uma.jmetal.component.examples.multiobjective.nsgaii
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ClassesClassDescriptionClass to configure and run the NSGA-II algorithm using a
GDominanceComparator, which allows to empower NSGA-II with a preference articulation mechanism based on reference point.Class to configure and run the NSGA-II algorithm using aGDominanceComparator, which allows to empower NSGA-II with a preference articulation mechanism based on reference point.Class to configure and run the NSGA-II algorithm configured with standard settings for solving a binary problem (OneZeroMaxis a multi-objective variant of OneMax).Class to configure and run the NSGA-II algorithm to solve a bi-objective TSP.Class to configure and run the NSGA-II algorithm to solve a bi-objective TSP.Class to configure and run the NSGA-II algorithm configured with standard settings.Class to configure and run the NSGA-II-DE algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm configured with standard settings for solving a binary problem (OneZeroMaxis a multi-objective variant of OneMax).Class to configure and run the NSGA-II algorithm to solve a bi-objective TSP.Class to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm configured with standard settings for solving a binary problem (OneZeroMaxis a multi-objective variant of OneMax).Class to configure a steady-state version of NSGA-IIClass to configure a steady-state version of NSGA-II, showing the current population during the execution of the algorithmClass to configure and run the NSGA-II algorithm with a stopping condition based on finding a Pareto front approximation having a hypervolume value higher than the 95% of the hypervolume of the reference front.Class to configure and run the NSGA-II algorithm with a stopping condition based on pressing a key.Class to configure and run the NSGA-II algorithm with a stopping condition based a maximum computing time.Class to configure and run the NSGA-II algorithm configured a bounded external archive that uses the crowding distance to remove solutions when the archive gets full.Class to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm to solve a problem having a mixed-encoding.Class to configure and run the NSGA-II algorithm configured with the ranking method known as Merge non-dominated sorting ranking (DOI: https://doi.org/10.1109/TCYB.2020.2968301)Class to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm to solve a bi-objective problem and plotting the result front with Smile (https://haifengl.github.io/)Class to configure and run the NSGA-II algorithm to solve a three-objective problem and plotting the result front with Smile (https://haifengl.github.io/)Class to configure and run the NSGA-II algorithm showing the population while the algorithm is runningClass to configure and run the NSGA-II algorithm using an unbounded archive that stores the non-dominated solutions found during the search.Class to configure and run the NSGA-II algorithm using theMultiThreadedEvaluationevaluator.