Nonlinear marine predator algorithm: A cost-effective optimizer for fair power allocation in NOMA-VLC-B5G networks
dc.contributor.author | Sadiq, Ali Safaa | |
dc.contributor.author | Dekhordi, Amin Abdollahi | |
dc.contributor.author | Mirjalili, Seyedali | |
dc.contributor.author | Pham, Quoc Viet | |
dc.date.accessioned | 2022-04-28T14:34:07Z | |
dc.date.available | 2022-04-28T14:34:07Z | |
dc.date.issued | 2022-05-11 | |
dc.identifier.citation | Sadiq, A.S., Dekhordi, A.A., Mirjalili, S. and Pham, Q.V. (2022) Nonlinear marine predator algorithm: A cost-effective optimizer for fair power allocation in NOMA-VLC-B5G networks. Expert Systems with Applications, 203, 117395. | en |
dc.identifier.issn | 0957-4174 | en |
dc.identifier.doi | 10.1016/j.eswa.2022.117395 | |
dc.identifier.uri | http://hdl.handle.net/2436/624730 | |
dc.description | © 2022 The Authors. Published by Elsevier. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1016/j.eswa.2022.117395 | en |
dc.description.abstract | This paper is 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. | en |
dc.format | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | Elsevier | en |
dc.relation.url | https://www.sciencedirect.com/science/article/abs/pii/S0957417422007400 | en |
dc.subject | Beyond-5G networks | en |
dc.subject | meta-heuristic | en |
dc.subject | optimization | en |
dc.subject | nonlinear theory | en |
dc.subject | Marin Predator algorithm | en |
dc.title | Nonlinear marine predator algorithm: A cost-effective optimizer for fair power allocation in NOMA-VLC-B5G networks | en |
dc.type | Journal article | en |
dc.identifier.journal | Expert Systems with Applications | en |
dc.date.updated | 2022-04-25T21:31:04Z | |
dc.identifier.articlenumber | 117395 | |
dc.date.accepted | 2022-04-25 | |
rioxxterms.funder | University of Wolverhampton | en |
rioxxterms.identifier.project | UOW28042022AS | en |
rioxxterms.version | VoR | en |
rioxxterms.licenseref.uri | https://creativecommons.org/licenses/by/4.0/ | en |
rioxxterms.licenseref.startdate | 2023-05-11 | en |
dc.source.volume | 203 | |
refterms.dateFCD | 2022-04-28T14:33:37Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2022-05-11T00:00:00Z |