FDS: Fractal decomposition based direct search approach for continuous dynamic optimization

Simple item page
dc.contributor.authorLlanza, Arcadi en_US
dc.contributor.authorShvai, Nadiya en_US
dc.contributor.authorNakib, Amir en_US
dc.date.accessioned2026-06-11T07:14:06Z
dc.date.available2026-06-11T07:14:06Z
dc.date.issued2025
dc.description.abstractDynamic optimization problems (DOPs) are known to be challenging due to the variability of their objective functions and constraints over time. The complexity of these problems increases further when the frequency of landscape change and the dimensionality of the search space are large. In this work, we propose a novel fractal decomposition-based method designed for DOPs, called FDS. It is a new single solution metaheuristic that introduces a new hyperspherebased space decomposition for efficient exploration, an archive for diversity control, and a pseudo-gradient-based local search (called GraILS) for fast exploitation. Extensive experiments on the well-known and the standard benchmark (the Moving Peak Benchmark: MPB) demonstrate that FDS consistently outperforms state-of-the-art competitors. Furthermore, FDS shows high robustness across diverse scenarios, maintaining superior performance despite variations in key benchmark parameters, such as the severity of landscape shifts, the number of peaks, the dimensionality of the problem, and the frequency of change. FDS achieves the highes average rank across all experiments and demonstrates dominant performance in 19 out of 23 scenarios. The implementation of FDS is available via the following GitHub repository: https:// github.com/alc1218/FDS. en_US
dc.identifier.citation111 en_US
dc.identifier.issn0020-0255
dc.identifier.issn1872-6291
dc.identifier.urihttps://ekmair.ukma.edu.ua/handle/123456789/40034
dc.identifier.urihttps://doi.org/10.1016/j.ins.2025.122237
dc.language.isoenen_US
dc.relation.sourceInformation Sciences en_US
dc.statusfirst published en_US
dc.subjectmetaheuristics en_US
dc.subjectdynamic optimization en_US
dc.subjectblack-box optimization en_US
dc.subjectfractal decomposition en_US
dc.subjectcontinuous optimization en_US
dc.subjectarticle en_US
dc.titleFDS: Fractal decomposition based direct search approach for continuous dynamic optimization en_US
dc.typeArticle en_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
FDS_Fractal_decomposition_based_direct_search_approach_for_continuous_dynamic_optimization.pdf
Size:
4.37 MB
Format:
Adobe Portable Document Format
Download
Collections
Кафедра математики