An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks

Nature-inspired algorithms serve as the backbone of modern computing technology, and over the past three decades, the field has grown enormously. Many applications were solved by such algorithms and are replacing the traditional classical optimization processes. A recent naked mole-rat algorithm (NM...

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Autores principales:	Pratap Singh, Rishi Pal Singh, Yudhvir Singh, Jana Shafi, Muhammad Fazal Ijaz
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	nature-inspired algorithms evolutionary algorithms swarm intelligent algorithms NMRA wireless underground sensor network distributed protocol Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/930f49a8e2b9425b817a945c738913a6
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id	oai:doaj.org-article:930f49a8e2b9425b817a945c738913a6
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spelling	oai:doaj.org-article:930f49a8e2b9425b817a945c738913a62021-11-25T18:17:26ZAn Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks10.3390/math92229422227-7390https://doaj.org/article/930f49a8e2b9425b817a945c738913a62021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2942https://doaj.org/toc/2227-7390Nature-inspired algorithms serve as the backbone of modern computing technology, and over the past three decades, the field has grown enormously. Many applications were solved by such algorithms and are replacing the traditional classical optimization processes. A recent naked mole-rat algorithm (NMRA) was proposed based on the mating patterns of naked mole-rats. This algorithm proved its worth in terms of competitiveness and application to various domains of research. The aim was to propose an algorithm based on NMRA, named enhanced NMRA (ENMRA), by mitigating the problems that this algorithm suffers from: slow convergence, poor exploration, and local optima stagnation. To enhance the exploration capabilities of basic NMRA, grey wolf optimization (GWO)-based search equations were employed. Exploitation was improved using population division methods based on local neighborhood search (LNS) and differential evolution (DE) equations. To avoid the local stagnation problem, a neighborhood search strategy around the best individual was utilized. Such improvements help the new variant to solve highly challenging optimization problems in contrast to existing algorithms. The efficacy of ENMRA was evaluated using CEC 2019 benchmark test suite. The results were statistically analyzed by the Wilcoxon rank-sum test and Friedman rank (f-rank) test. The resulting analysis proved that ENMRA is superior to the competitive algorithms for test functions CEC 2019 with overall effectiveness of 60.33%. Moreover, the real-world optimization problem from underground wireless sensor networks for an efficient cross-layer solution was also used to test the efficiency of ENMRA. The results of comparative study and statistical tests affirmed the efficient performance of the proposed algorithm.Pratap SinghRishi Pal SinghYudhvir SinghJana ShafiMuhammad Fazal IjazMDPI AGarticlenature-inspired algorithmsevolutionary algorithmsswarm intelligent algorithmsNMRAwireless underground sensor networkdistributed protocolMathematicsQA1-939ENMathematics, Vol 9, Iss 2942, p 2942 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	nature-inspired algorithms evolutionary algorithms swarm intelligent algorithms NMRA wireless underground sensor network distributed protocol Mathematics QA1-939
spellingShingle	nature-inspired algorithms evolutionary algorithms swarm intelligent algorithms NMRA wireless underground sensor network distributed protocol Mathematics QA1-939 Pratap Singh Rishi Pal Singh Yudhvir Singh Jana Shafi Muhammad Fazal Ijaz An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
description	Nature-inspired algorithms serve as the backbone of modern computing technology, and over the past three decades, the field has grown enormously. Many applications were solved by such algorithms and are replacing the traditional classical optimization processes. A recent naked mole-rat algorithm (NMRA) was proposed based on the mating patterns of naked mole-rats. This algorithm proved its worth in terms of competitiveness and application to various domains of research. The aim was to propose an algorithm based on NMRA, named enhanced NMRA (ENMRA), by mitigating the problems that this algorithm suffers from: slow convergence, poor exploration, and local optima stagnation. To enhance the exploration capabilities of basic NMRA, grey wolf optimization (GWO)-based search equations were employed. Exploitation was improved using population division methods based on local neighborhood search (LNS) and differential evolution (DE) equations. To avoid the local stagnation problem, a neighborhood search strategy around the best individual was utilized. Such improvements help the new variant to solve highly challenging optimization problems in contrast to existing algorithms. The efficacy of ENMRA was evaluated using CEC 2019 benchmark test suite. The results were statistically analyzed by the Wilcoxon rank-sum test and Friedman rank (f-rank) test. The resulting analysis proved that ENMRA is superior to the competitive algorithms for test functions CEC 2019 with overall effectiveness of 60.33%. Moreover, the real-world optimization problem from underground wireless sensor networks for an efficient cross-layer solution was also used to test the efficiency of ENMRA. The results of comparative study and statistical tests affirmed the efficient performance of the proposed algorithm.
format	article
author	Pratap Singh Rishi Pal Singh Yudhvir Singh Jana Shafi Muhammad Fazal Ijaz
author_facet	Pratap Singh Rishi Pal Singh Yudhvir Singh Jana Shafi Muhammad Fazal Ijaz
author_sort	Pratap Singh
title	An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
title_short	An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
title_full	An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
title_fullStr	An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
title_full_unstemmed	An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks
title_sort	enhanced naked mole rat algorithm for optimal cross-layer solution for wireless underground sensor networks
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/930f49a8e2b9425b817a945c738913a6
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An Enhanced Naked Mole Rat Algorithm for Optimal Cross-Layer Solution for Wireless Underground Sensor Networks

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