Enhancing exploration and exploitation of NSGA-II with GP and PDL

Peter David Shannon, Chrystopher L. Nehaniv, Somnuk Phon-Amnuaisuk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


In this paper, we show that NSGA-II can be applied to GP and the Process Description Language (PDL) and describe two modifications to NSGA-II. The first modification removes individuals which have the same behaviour from GP populations. It selects for de-duplication by taking the result of each objective fitness function together to make a comparison. NSGA-II is designed to expand its Pareto front of solutions by favouring individuals who have the highest or lowest value (boundary points) in a front, for any objective. The second modification enhances exploitation by preferring individuals who occupy an extreme position for most objective fitness functions. The results show, for the first time, that NSGA-II can be used with PDL and GP to successfully solve a robot control problem and that the suggested modifications offer significant improvements over an algorithm used previously with GP and PDL and unmodified NSGA-II for our test problem.

Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - 8th International Conference, ICSI 2017, Proceedings
PublisherSpringer Nature
Number of pages13
Volume10385 LNCS
ISBN (Print)9783319618234
Publication statusE-pub ahead of print - 24 Jun 2017
Event8th International Conference on Swarm Intelligence, ICSI 2017 - Fukuoka, Japan
Duration: 27 Jul 20171 Aug 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10385 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


Conference8th International Conference on Swarm Intelligence, ICSI 2017


  • Exploration and exploitation
  • Genetic programming
  • Process description language


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