Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Stapleton:2021:CEC,

• author = "Fergal Stapleton and Edgar Galvan",
• booktitle = "2021 IEEE Congress on Evolutionary Computation (CEC)",
• title = "Semantic Neighborhood Ordering in Multi-objective Genetic Programming based on Decomposition",
• year = "2021",
• editor = "Yew-Soon Ong",
• pages = "580--587",
• address = "Krakow, Poland",
• month = "28 " # jun # "-1 " # jul,
• isbn13 = "978-1-7281-8393-0",
• abstract = "Semantic diversity in Genetic Programming has proved to be highly beneficial in evolutionary search. We have witnessed a surge in the number of scientific works in the area, starting first in discrete spaces and moving then to continuous spaces. The vast majority of these works, however, have focused their attention on single-objective genetic programming paradigms, with a few exceptions focusing on Evolutionary Multi-objective Optimization (EMO). The latter works have used well-known robust algorithms, including the Non-dominated Sorting Genetic Algorithm II and the Strength Pareto Evolutionary Algorithm, both heavily influenced by the notion of Pareto dominance. These inspiring works led us to make a step forward in EMO by considering Multi-objective Evolutionary Algorithms Based on Decomposition (MOEA/D). We show, for the first time, how we can naturally promote semantic diversity in MOEA/D in Genetic Programming.",
• keywords = "genetic algorithms, genetic programming, Systematics, Semantics, Sociology, Evolutionary computation, Ions, Surges, Semantics, Multi-objective Evolutionary Algorithms Based on Decomposition, Unbalanced data",
• DOI = "doi:10.1109/CEC45853.2021.9504860",
• notes = "Also known as \cite{9504860}",

}

Genetic Programming entries for Fergal Stapleton Edgar Galvan Lopez

Citations