An accurate partially attracted firefly algorithm
The firefly algorithm (FA) is a new and powerful algorithm for optimization. However, it has the disadvantages of high computational complexity and low convergence accuracy, especially when solving complex problems. In this paper, an accurate partially attracted firefly algorithm (PaFA) is proposed...
Saved in:
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/139039 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | The firefly algorithm (FA) is a new and powerful algorithm for optimization. However, it has the disadvantages of high computational complexity and low convergence accuracy, especially when solving complex problems. In this paper, an accurate partially attracted firefly algorithm (PaFA) is proposed by adopting a partial attraction model and a fast attractiveness calculation strategy. The partial attraction model can preserve swarm diversity and make full use of individual information. The fast attractiveness calculation strategy ensures information sharing among the individuals and it also improves the convergence accuracy. The experimental results demonstrate the good performance of PaFA in terms of the solution accuracy compared with two state-of-the-art FA variants and two other bio-inspired algorithms. |
|---|