Application of Multidimensional ACO Pheromone for Multi-Objective Optimization
Abstract In this work, we investigate an approach that enriches the information encoded within the ACO pheromone structure in order to enhance the performance of swarm optimization. While this concept has been extensively studied in the context of single-objective optimization, this paper provides a comprehensive evaluation of its extension to multi-objective optimization problems. The results demonstrate that this enhanced pheromone representation remains effective in multi-objective settings.
Authors
- Grażyna Starzec (ORCID: https://orcid.org/0000-0002-0813-798X)
- Małgorzata Zajęcka (ORCID: https://orcid.org/0009-0009-7914-2653)
- Danuta Rutkowska (ORCID: https://orcid.org/0000-0003-0217-2589)
- Aleksander Byrski (ORCID: https://orcid.org/0000-0001-6317-7012)
- Mateusz Starzec (ORCID: https://orcid.org/0000-0001-8258-2443)
- El‐Ghazali Talbi (ORCID: https://orcid.org/0000-0003-4549-1010)
Institutions
- Université de Lille (FR)
- University of Agriculture in Krakow (PL)
- University of Łódź (PL)
- AGH University of Krakow (PL)
Publication Details
- Journal
- Journal of Artificial Intelligence and Soft Computing Research
- Published
- 2026-07-01
- DOI
- https://doi.org/10.2478/jaiscr-2026-0022
- Primary Topic
- Advanced Multi-Objective Optimization Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00