A survey on dynamic populations in bio-inspired algorithms
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Farinati:2024:GPEM,
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author = "Davide Farinati and Leonardo Vanneschi",
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title = "A survey on dynamic populations in bio-inspired
algorithms",
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journal = "Genetic Programming and Evolvable Machines",
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year = "2024",
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volume = "25",
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number = "2",
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pages = "Article no 19",
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month = dec,
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keywords = "genetic algorithms, genetic programming,
Population-based algorithms, Bio-inspired algorithms,
Population size, Dynamic population, Adaptive
population",
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ISSN = "1389-2576",
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URL = "https://rdcu.be/dOTDV",
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DOI = "doi:10.1007/s10710-024-09492-4",
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size = "32 pages",
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abstract = "... a significant amount of computational effort in
phases where the evolution is functioning well, and
therefore a large population is not needed. This allows
for reusing the previously saved computational effort
when optimization becomes more challenging, and hence a
greater computational effort is required. Numerous past
contributions have demonstrated a notable advantage of
using dynamically sized populations, often resulting in
comparable results to those obtained by the standard
PBBIAs but with a significant saving of computational
effort. However, despite the numerous successes that
have been presented, to date, there is still no
comprehensive collection of past contributions on the
use of dynamic populations that allows for their
categorization and critical analysis. This article aims
to bridge this gap by presenting a systematic
literature review regarding the use of dynamic
populations in PBBIAs, as well as identifying gaps in
the research that can lead the path to future works.",
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notes = "NOVA Information Management School (NOVA IMS),
Universidade Nova de Lisboa, Campus de Campolide,
1070-312, Lisboa, Portugal",
- }
Genetic Programming entries for
Davide Farinati
Leonardo Vanneschi
Citations