Nonlinear Marine Predator Algorithm (NMPA)
Version 1.0.0 (447 KB) by
Ali Sadiq
A Cost-effective Optimizer for Fair Power Allocation in NOMA-VLC-B5G Networks
NMPA an influential attempt to identify and alleviate some of the issues with the recently proposed optimization technique called the Marine Predator Algorithm (MPA). With a visual investigation of its exploratory and exploitative behavior, it is observed that the transition of search from being global to local can be further improved. As an extremely cost-effective method, a set of nonlinear functions is used to change the search patterns of the MPA algorithm. The proposed algorithm is called Nonlinear Marin Predator Algorithm (NMPA) is tested on a set of benchmark functions. A comprehensive comparative study shows the superiority of the proposed method compared to the original MPA and even other recent meta-heuristics. The paper also considers solving a real-world case study around power allocation in non-orthogonal multiple access (NOMA) and visible light communications (VLC) for Beyond 5G (B5G) networks to showcase the applicability of the NMPA algorithm. NMPA algorithm shows its superiority in solving a wide range of benchmark functions as well as obtaining fair power allocation for multiple users in NOMA-VLC-B5G systems compared with the state-of-the-art algorithms.
In case you can't access the paper, please email me on ali.sadiq@wlv.ac.uk or alisafa09@gmail.com and I will get back to you soon.
Cite As
Ali Sadiq (2024). Nonlinear Marine Predator Algorithm (NMPA) (https://www.mathworks.com/matlabcentral/fileexchange/111135-nonlinear-marine-predator-algorithm-nmpa), MATLAB Central File Exchange. Retrieved .
Sadiq, Ali Safaa, et al. “Nonlinear Marine Predator Algorithm: A Cost-Effective Optimizer for Fair Power Allocation in NOMA-VLC-B5G Networks.” Expert Systems with Applications, Elsevier BV, May 2022, p. 117395, doi:10.1016/j.eswa.2022.117395.
MATLAB Release Compatibility
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R2022a
Compatible with any release
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Acknowledgements
Inspired by: Marine Predators Algorithm (MPA)
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1.0.0 |