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A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems

Mas’ud, Abdullahi Abubakar; Salawudeen, Ahmed T.; Umar, Abubakar A.; Shaaban, Yusuf A.; Muhammad-Sukki, Firdaus; Musa, Umar; Alshammari, Saud J.

Authors

Abdullahi Abubakar Mas’ud

Ahmed T. Salawudeen

Abubakar A. Umar

Yusuf A. Shaaban

Umar Musa

Saud J. Alshammari



Abstract

The Quasi oppositional smell agent optimization (QOBL-SAO) and its levy flight variant (LFQOBL-SAO) are two cutting-edge software tools for optimizing PV/wind/battery power systems. They can also be used to solve real-world CEC2020 optimization problems and are as good as top-performing software such as IUDE, MAgES and the iLSHAD ɛ. The QOBL-SAO exploits the random mode’s weakness and then adds a number to the initial population. The LFQOBL-SAO, on the other hand, improves the random mode’s weakness in order to solve this problem. The LFQOBL-SAO improves performance and search space by using levy flight instead of random code.

Citation

Mas’ud, A. A., Salawudeen, A. T., Umar, A. A., Shaaban, Y. A., Muhammad-Sukki, F., Musa, U., & Alshammari, S. J. (2024). A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems. Software Impacts, 19, Article 100630. https://doi.org/10.1016/j.simpa.2024.100630

Journal Article Type Article
Acceptance Date Feb 17, 2024
Online Publication Date Feb 23, 2024
Publication Date 2024-03
Deposit Date Feb 26, 2024
Publicly Available Date Feb 26, 2024
Journal Software Impacts
Electronic ISSN 2665-9638
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 19
Article Number 100630
DOI https://doi.org/10.1016/j.simpa.2024.100630
Keywords Smell agent optimization; Levy flight smell agent optimization; Quasi oppositional smell agent optimization
Public URL http://researchrepository.napier.ac.uk/Output/3524028
Publisher URL https://www.sciencedirect.com/science/article/pii/S2665963824000186

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