An adaptive multi-team perturbation-guiding Jaya algorithm for optimization and its applications
Authors:
- R. Venkata Rao,
- Hameer Singh Keesari,
- P. Ocłoń,
- Jan Taler
Abstract
This study proposes an adaptive multi-team perturbation-guiding Jaya (AMTPG-Jaya) algorithm which uses multiple teams to explore the search space. The proposed algorithm adapts the number of teams to explore the search space based on the convergence to the optimum. Furthermore, each team uses the same set of the population, and there is a different perturbation or movement equation for each team. As each team has a different perturbation scheme, the set of the moves to new positions by each team is unique. The moving equation of the worst performing team will be updated by the superiority of solutions produced by each team. The superiority of the solutions for each team is calculated based on the fitness value and boundary violations of solutions. The proposed algorithm is examined using computationally expensive constrained optimization problems taken from the CEC-2017 technical report. Computational test results have demonstrated the effectiveness of the AMTPG-Jaya algorithm when compared to the other well-known approaches. Also, a multi-objective optimization is carried out on a solar dish Stirling engine system to find the optimal thermo-economic parameters to maximize dimensionless power and thermal efficiency. The computational results revealed that the AMTPG-Jaya algorithm results are superior to those achieved by the other algorithms presented in this work.
- Record ID
- CUT986cf63d263b490985d32419dcbb946c
- Publication categories
- ;
- Author
- Journal series
- Engineering with Computers, ISSN 0177-0667, e-ISSN 1435-5663
- Issue year
- 2020
- Vol
- 36
- No
- 1
- Pages
- 391-419
- Other elements of collation
- rys.; tab.; wykr.; Bibliografia (na s.) - 417-419; Bibliografia (liczba pozycji) - 56; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 36, Iss. 1
- Keywords in English
- adaptive multi-team perturbation, AMTPG-Jaya, Jaya algorithm, multi-objective optimization
- DOI
- DOI:10.1007/s00366-019-00706-3 Opening in a new tab
- URL
- https://link.springer.com/article/10.1007/s00366-019-00706-3 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 70
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT986cf63d263b490985d32419dcbb946c/
- URN
urn:pkr-prod:CUT986cf63d263b490985d32419dcbb946c
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.