Abstract
Metaheuristics are found to be efficient in different applications where the use of exact algorithms becomes short-handed. In the last decade, many of these algorithms have been introduced and used in a wide range of applications. Nevertheless, most of those approaches share similar components leading to a concern related to their novelty or contribution. Thus, in this paper, a pool template is proposed and used to categorize algorithm components permitting to analyze them in a structured way. We exemplify its use by means of continuous optimization metaheuristics, and provide some measures and methodology to identify their similarities and novelties. Finally, a discussion at a component level is provided in order to point out possible design differences and commonalities.
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Notes
We should note that the archiving function may be extended in the sense of distinguishing long-term memory and short-term memory functions, the first accounting for recent solutions or solution attributes and the latter accounting for measures supporting to memorize an overall history of a search, e.g., by using frequency-based memory to count for occurrences of properties of solutions.
For this comparison, we rely on Algorithm 3 presented Weyland (2015).
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Acknowledgements
This work was partially supported by the Ministry of Science, Innovation and Universities of the Government of Spain AEI/FEDER through the project RTI2018-095197-B-I00. Surafel Luleseged Tilahun would like to acknowledge the TWAS-DFG Cooperation Visits Programme for the support to visit University of Hamburg for a research collaboration.
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de Armas, J., Lalla-Ruiz, E., Tilahun, S.L. et al. Similarity in metaheuristics: a gentle step towards a comparison methodology. Nat Comput 21, 265–287 (2022). https://doi.org/10.1007/s11047-020-09837-9
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DOI: https://doi.org/10.1007/s11047-020-09837-9