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Article

A Modified Coronavirus Herd Immunity Optimizer for the Power Scheduling Problem

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Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman 346, United Arab Emirates
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Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, Irbid 21110, Jordan
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Department of Computer Science, Al-Aqsa University, P.O. Box 4051, Gaza P860, Palestine
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Artificial Intelligence Research Center (AIRC), Ajman University, Ajman 346, United Arab Emirates
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School of Computer Sciences, Universiti Sains Malaysia, Gelugor 11800, Malaysia
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Information Technology Research and Development Center (ITRDC), University of Kufa, Kufa 54001, Iraq
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Computing Department, College of Engineering and Applied Sciences, American University of Kuwait, Salmiya 20002, Kuwait
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Computer Science Department, Yarmouk University, Irbid 21163, Jordan
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MLALP Research Group, University of Sharjah, Sharjah 346, United Arab Emirates
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Department of Applied Informatics, Vytautas Magnus University, 44404 Kaunas, Lithuania
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College of Computer Science and Information Technology, University of Anbar, Anbar 31001, Iraq
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Author to whom correspondence should be addressed.
Academic Editors: Sambor Guze and Enrico Zio
Mathematics 2022, 10(3), 315; https://doi.org/10.3390/math10030315
Received: 17 November 2021 / Revised: 7 January 2022 / Accepted: 11 January 2022 / Published: 20 January 2022
(This article belongs to the Special Issue Mathematical Modelling and Multi-Criteria Optimisation in Engineering)
The Coronavirus herd immunity optimizer (CHIO) is a new human-based optimization algorithm that imitates the herd immunity strategy to eliminate of the COVID-19 disease. In this paper, the coronavirus herd immunity optimizer (CHIO) is modified to tackle a discrete power scheduling problem in a smart home (PSPSH). PSPSH is a combinatorial optimization problem with NP-hard features. It is a highly constrained discrete scheduling problem concerned with assigning the operation time for smart home appliances based on a dynamic pricing scheme(s) and several other constraints. The primary objective when solving PSPSH is to maintain the stability of the power system by reducing the ratio between average and highest power demand (peak-to-average ratio (PAR)) and reducing electricity bill (EB) with considering the comfort level of users (UC). This paper modifies and adapts the CHIO algorithm to deal with such discrete optimization problems, particularly PSPSH. The adaptation and modification include embedding PSPSH problem-specific operators to CHIO operations to meet the discrete search space requirements. PSPSH is modeled as a multi-objective problem considering all objectives, including PAR, EB, and UC. The proposed method is examined using a dataset that contains 36 home appliances and seven consumption scenarios. The main CHIO parameters are tuned to find their best values. These best values are used to evaluate the proposed method by comparing its results with comparative five metaheuristic algorithms. The proposed method shows encouraging results and almost obtains the best results in all consumption scenarios. View Full-Text
Keywords: discrete coronavirus herd immunity optimizer; power scheduling problem in smart home; multi-criteria optimisation; smart home; multi-objective optimisation problem discrete coronavirus herd immunity optimizer; power scheduling problem in smart home; multi-criteria optimisation; smart home; multi-objective optimisation problem
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MDPI and ACS Style

Makhadmeh, S.N.; Al-Betar, M.A.; Awadallah, M.A.; Abasi, A.K.; Alyasseri, Z.A.A.; Doush, I.A.; Alomari, O.A.; Damaševičius, R.; Zajančkauskas, A.; Mohammed, M.A. A Modified Coronavirus Herd Immunity Optimizer for the Power Scheduling Problem. Mathematics 2022, 10, 315. https://doi.org/10.3390/math10030315

AMA Style

Makhadmeh SN, Al-Betar MA, Awadallah MA, Abasi AK, Alyasseri ZAA, Doush IA, Alomari OA, Damaševičius R, Zajančkauskas A, Mohammed MA. A Modified Coronavirus Herd Immunity Optimizer for the Power Scheduling Problem. Mathematics. 2022; 10(3):315. https://doi.org/10.3390/math10030315

Chicago/Turabian Style

Makhadmeh, Sharif Naser, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Ammar Kamal Abasi, Zaid Abdi Alkareem Alyasseri, Iyad Abu Doush, Osama Ahmad Alomari, Robertas Damaševičius, Audrius Zajančkauskas, and Mazin Abed Mohammed. 2022. "A Modified Coronavirus Herd Immunity Optimizer for the Power Scheduling Problem" Mathematics 10, no. 3: 315. https://doi.org/10.3390/math10030315

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