A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application
The Fruit Fly Optimization Algorithm is a swarm intelligence algorithm with strong versatility and high computational efficiency. However, when faced with complex multi-peak problems, Fruit Fly Optimization Algorithm tends to converge prematurely. In response to this situation, this article proposes...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-02-01
|
| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/15501477211073037 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832556825513295872 |
|---|---|
| author | Ru-Yu Wang Pei Hu Chia-Cheng Hu Jeng-Shyang Pan |
| author_facet | Ru-Yu Wang Pei Hu Chia-Cheng Hu Jeng-Shyang Pan |
| author_sort | Ru-Yu Wang |
| collection | DOAJ |
| description | The Fruit Fly Optimization Algorithm is a swarm intelligence algorithm with strong versatility and high computational efficiency. However, when faced with complex multi-peak problems, Fruit Fly Optimization Algorithm tends to converge prematurely. In response to this situation, this article proposes a new optimized structure—Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm. The new algorithm uses the evolution matrix in QUasi-Affine TRansformation Evolution algorithm to update the position coordinates of particles. This strategy makes the movement of particles more scientific and the search space broader. In order to prove its effectiveness, we compare Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm with five other mature intelligent algorithms, and test them on 22 different types of benchmark functions. In order to observe the multi-faceted performance of Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm more intuitively, we also conduct experiments on algorithm convergence analysis, the Friedman test, the Wilcoxon signed-rank test, and running time comparison. Through the above several comparative experiments, Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm has indeed demonstrated its strong competitiveness. Finally, we apply it to Capacitated Vehicle Routing Problem. Through comparing with the contrast algorithms, it is confirmed that Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm can achieve better vehicle routes planning. |
| format | Article |
| id | doaj-art-7d84b731daa1441abfa9b3466325c833 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2022-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-7d84b731daa1441abfa9b3466325c8332025-02-03T05:44:19ZengWileyInternational Journal of Distributed Sensor Networks1550-14772022-02-011810.1177/15501477211073037A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and applicationRu-Yu Wang0Pei Hu1Chia-Cheng Hu2Jeng-Shyang Pan3College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, ChinaSchool of Software, Nanyang Institute of Technology, Nanyang, ChinaCollege of Artificial Intelligence, Yango University, Fuzhou, ChinaDepartment of Information Management, Chaoyang University of Technology, TaichungThe Fruit Fly Optimization Algorithm is a swarm intelligence algorithm with strong versatility and high computational efficiency. However, when faced with complex multi-peak problems, Fruit Fly Optimization Algorithm tends to converge prematurely. In response to this situation, this article proposes a new optimized structure—Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm. The new algorithm uses the evolution matrix in QUasi-Affine TRansformation Evolution algorithm to update the position coordinates of particles. This strategy makes the movement of particles more scientific and the search space broader. In order to prove its effectiveness, we compare Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm with five other mature intelligent algorithms, and test them on 22 different types of benchmark functions. In order to observe the multi-faceted performance of Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm more intuitively, we also conduct experiments on algorithm convergence analysis, the Friedman test, the Wilcoxon signed-rank test, and running time comparison. Through the above several comparative experiments, Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm has indeed demonstrated its strong competitiveness. Finally, we apply it to Capacitated Vehicle Routing Problem. Through comparing with the contrast algorithms, it is confirmed that Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm can achieve better vehicle routes planning.https://doi.org/10.1177/15501477211073037 |
| spellingShingle | Ru-Yu Wang Pei Hu Chia-Cheng Hu Jeng-Shyang Pan A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application International Journal of Distributed Sensor Networks |
| title | A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application |
| title_full | A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application |
| title_fullStr | A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application |
| title_full_unstemmed | A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application |
| title_short | A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application |
| title_sort | novel fruit fly optimization algorithm with quasi affine transformation evolutionary for numerical optimization and application |
| url | https://doi.org/10.1177/15501477211073037 |
| work_keys_str_mv | AT ruyuwang anovelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT peihu anovelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT chiachenghu anovelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT jengshyangpan anovelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT ruyuwang novelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT peihu novelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT chiachenghu novelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication AT jengshyangpan novelfruitflyoptimizationalgorithmwithquasiaffinetransformationevolutionaryfornumericaloptimizationandapplication |