- Tytuł:
- Gold rush optimizer : a new population-based metaheuristic algorithm
- Autorzy:
- Zolf, Kamran
- Powiązania:
- https://bibliotekanauki.pl/articles/2204102.pdf
- Data publikacji:
- 2023
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
gold rush optimizer
metaheuristic
global optimization
population-based algorithm - Opis:
- Today’s world is characterised by competitive environments, optimal resource utilization, and cost reduction, which has resulted in an increasing role for metaheuristic algorithms in solving complex modern problems. As a result, this paper introduces the gold rush optimizer (GRO), a population-based metaheuristic algorithm that simulates how gold-seekers prospected for gold during the Gold Rush Era using three key concepts of gold prospecting: migration, collaboration, and panning. The GRO algorithm is compared to twelve well-known metaheuristic algorithms on 29 benchmark test cases to assess the proposed approach’s performance. For scientific evaluation, the Friedman and Wilcoxon signed-rank tests are used. In addition to these test cases, the GRO algorithm is evaluated using three real-world engineering problems. The results indicated that the proposed algorithm was more capable than other algorithms in proposing qualitative and competitive solutions.
- Źródło:
-
Operations Research and Decisions; 2023, 33, 1; 113--150
2081-8858
2391-6060 - Pojawia się w:
- Operations Research and Decisions
- Dostawca treści:
- Biblioteka Nauki
Artykuł