Abstract
A novel nature-inspired metaheuristic optimization algorithm, called the quantum firefly algorithm, is proposed in this paper. The algorithm imitates (a) the social behaviour of fireflies mating in nature, (b) laws of quantum physics, and (c) laws of natural evolution. The algorithm combines the powers of two well-known algorithms: the firefly algorithm and the quantum genetic algorithm. The proposed quantum firefly algorithm’s performance is tested on 15 mathematical test functions and one structural design problem. The obtained results show that the quantum firefly algorithm is very competitive compared to the firefly algorithm and the quantum genetic algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 8741-8759 |
| Number of pages | 19 |
| Journal | Arabian Journal for Science and Engineering |
| Volume | 46 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - Sept 2021 |
Keywords
- Firefly algorithm
- Global optimization
- Metaheuristics
- Quantum genetic algorithm
- Test functions
ASJC Scopus subject areas
- General