Application of Artificial Immune Networks in Continuous Function Optimizations
Abstract
This paper deals with the application of artificial immune networks in continuous
function optimizations. The performance of the immunological algorithms is analyzed using
the Optimization Algorithm Toolkit. It is shown that the CLIGA algorithm has, by far, the
fastest convergence and the best score - in terms of the number of required iterations, for the
analyzed continuous function. Also, based on the test results, it was concluded, that the lowest
total number of iterations for the defined run time was achieved with the opt-IA algorithm,
followed by the CLONALG and CLIGA algorithms.
Keywords:
artificial immune networks / Optimization Algorithm Toolkit / continuous function optimization / performanceSource:
Acta Polytechnica Hungarica, 2022, 19, 7, 153-164Publisher:
- Budapest : Óbuda University
Collections
Institution/Community
JakovTY - JOUR AU - Čisar, Petar AU - Maravić Čisar, Sanja AU - Popović, Brankica AU - Kuk, Kristijan AU - Vuković, Igor PY - 2022 UR - http://jakov.kpu.edu.rs/handle/123456789/1446 AB - This paper deals with the application of artificial immune networks in continuous function optimizations. The performance of the immunological algorithms is analyzed using the Optimization Algorithm Toolkit. It is shown that the CLIGA algorithm has, by far, the fastest convergence and the best score - in terms of the number of required iterations, for the analyzed continuous function. Also, based on the test results, it was concluded, that the lowest total number of iterations for the defined run time was achieved with the opt-IA algorithm, followed by the CLONALG and CLIGA algorithms. PB - Budapest : Óbuda University T2 - Acta Polytechnica Hungarica T1 - Application of Artificial Immune Networks in Continuous Function Optimizations VL - 19 IS - 7 SP - 153 EP - 164 DO - 10.12700/APH.19.7.2022.7.8 ER -
@article{ author = "Čisar, Petar and Maravić Čisar, Sanja and Popović, Brankica and Kuk, Kristijan and Vuković, Igor", year = "2022", abstract = "This paper deals with the application of artificial immune networks in continuous function optimizations. The performance of the immunological algorithms is analyzed using the Optimization Algorithm Toolkit. It is shown that the CLIGA algorithm has, by far, the fastest convergence and the best score - in terms of the number of required iterations, for the analyzed continuous function. Also, based on the test results, it was concluded, that the lowest total number of iterations for the defined run time was achieved with the opt-IA algorithm, followed by the CLONALG and CLIGA algorithms.", publisher = "Budapest : Óbuda University", journal = "Acta Polytechnica Hungarica", title = "Application of Artificial Immune Networks in Continuous Function Optimizations", volume = "19", number = "7", pages = "153-164", doi = "10.12700/APH.19.7.2022.7.8" }
Čisar, P., Maravić Čisar, S., Popović, B., Kuk, K.,& Vuković, I.. (2022). Application of Artificial Immune Networks in Continuous Function Optimizations. in Acta Polytechnica Hungarica Budapest : Óbuda University., 19(7), 153-164. https://doi.org/10.12700/APH.19.7.2022.7.8
Čisar P, Maravić Čisar S, Popović B, Kuk K, Vuković I. Application of Artificial Immune Networks in Continuous Function Optimizations. in Acta Polytechnica Hungarica. 2022;19(7):153-164. doi:10.12700/APH.19.7.2022.7.8 .
Čisar, Petar, Maravić Čisar, Sanja, Popović, Brankica, Kuk, Kristijan, Vuković, Igor, "Application of Artificial Immune Networks in Continuous Function Optimizations" in Acta Polytechnica Hungarica, 19, no. 7 (2022):153-164, https://doi.org/10.12700/APH.19.7.2022.7.8 . .