Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems
| Autor: | Farhad Soleimanian Gharehchopogh, Benyamin Abdollahzadeh, Seyedali Mirjalili |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Optimization problem
biology Wilcoxon signed-rank test Computer science Social intelligence Collective intelligence Gorilla Theoretical Computer Science Human-Computer Interaction Artificial Intelligence biology.animal Benchmark (computing) Metaheuristic Algorithm Software Statistical hypothesis testing |
| Zdroj: | International Journal of Intelligent Systems. 36:5887-5958 |
| ISSN: | 1098-111X 0884-8173 |
| DOI: | 10.1002/int.22535 |
| Popis: | Metaheuristics play a critical role in solving optimization problems, and most of them have been inspired by the collective intelligence of natural organisms in nature. This paper proposes a new metaheuristic algorithm inspired by gorilla troops' social intelligence in nature, called Artificial Gorilla Troops Optimizer (GTO). In this algorithm, gorillas' collective life is mathematically formulated, and new mechanisms are designed to perform exploration and exploitation. To evaluate the GTO, we apply it to 52 standard benchmark functions and seven engineering problems. Friedman's test and Wilcoxon rank-sum statistical tests statistically compared the proposed method with several existing metaheuristics. The results demonstrate that the GTO performs better than comparative algorithms on most benchmark functions, particularly on high-dimensional problems. The results demonstrate that the GTO can provide superior results compared with other metaheuristics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|