Fireworks Algorithm versus Plant Propagation Algorithm

Open Access
Authors
Publication date 2019
Host editors
  • J.J. Merelo
  • J. Garibaldi
  • A. Linares Barranco
  • K. Madani
  • K. Warwick
Book title IJCCI 2019
Book subtitle proceedings of the 11th International Joint Conference on Computational Intelligence : Vienna, Austria, September 17-19, 2019
ISBN
  • 9789897583841
Event 11th International Joint Conference on Computational Intelligence
Pages (from-to) 101-112
Publisher Setúbal: SciTePress Science and Technology Publications
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract
In recent years, the field of Evolutionary Algorithms has seen a tremendous increase in novel methods. While these algorithmic innovations often show excellent results on relatively limited domains, they are less often rigorously cross-tested or compared to other state-of-the-art developments. Two of these methods, quite similar in their appearance, are the Fireworks Algorithm and Plant Propagation Algorithm.
This study compares the similarities and differences between these two algorithms, from both quantitative and qualitative perspectives, by comparing them on a set of carefully chosen benchmark functions. The Fireworks Algorithm outperforms the Plant Propagation Algorithm on the majority of these, but when the functions are shifted slightly, Plant Propagation gives better results. Reasons behind these surprising differences are presented, and comparison methods for evolutionary algorithms are discussed in a wider context. All source code, graphs, test functions, and algorithmic implementations have been made publicly available for reference and further reuse.
Document type Conference contribution
Language English
Published at https://doi.org/10.5220/0008169401010112
Downloads
ECTA_2019_23 (Final published version)
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