Szczegóły publikacji
Opis bibliograficzny
Two-dimensional pheromone in ant colony optimization / Grażyna STARZEC, Mateusz STARZEC, Sanghamitra Bandyopadhyay, Ujjwal Maulik, Leszek RUTKOWSKI, Marek KISIEL-DOROHINICKI, Aleksander BYRSKI // W: Computational Collective Intelligence : 15th International Conference, ICCCI 2023 : Budapest, Hungary, September 27–29, 2023 : proceedings / eds. Ngoc Thanh Nguyen, [et al.]. — Cham : Springer Nature Switzerland, cop. 2023. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 14162. Lecture Notes in Artificial Intelligence). — ISBN: 978-3-031-41455-8 ; e-ISBN: 978-3-031-41456-5. — S. 459–471. — Bibliogr., Abstr. — L. Rutkowski - dod. afiliacja: Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Autorzy (7)
- AGHStarzec Grażyna
- AGHStarzec Mateusz
- Bandyopadhyay Sanghamitra
- Maulik Ujjwal
- AGHRutkowski Leszek
- AGHKisiel-Dorohinicki Marek
- AGHByrski Aleksander
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 149172 |
|---|---|
| Data dodania do BaDAP | 2024-07-30 |
| DOI | 10.1007/978-3-031-41456-5_35 |
| Rok publikacji | 2023 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computational Collective Intelligence: Semantic Web, Social Networks and Multiagent Systems 2023 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Ant Colony Optimization (ACO) is an acclaimed method for solving combinatorial problems proposed by Marco Dorigo in 1992 and has since been enhanced and hybridized many times. This paper proposes a novel modification of the algorithm, based on the introduction of a two-dimensional pheromone into a single-criteria ACO. The complex structure of the pheromone is supposed to increase ants’ awareness when choosing the next edge of the graph, helping them achieve better results than in the original algorithm. The proposed modification is general and thus can be applied to any ACO-type algorithm. We show the results based on a representative instance of TSPLIB and discuss them in order to support our claims regarding the efficiency and efficacy of the proposed approach.
