Methodology for modified whale optimization algorithm for solving appliances scheduling problem
Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectiv...
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| Format: | Article |
| Language: | English |
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Penerbit Akademia Baru
2020
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/27814/1/JARFMTS%2076%202%202020%20132%20143.pdf |
| _version_ | 1825805694327062528 |
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| author | Omar, Mohd Faizal Mohd Bakeri, Noorhadila Mohd Nawi, Mohd Nasrun Hairani, Norfazlirda Khalid, Khalizul |
| author_facet | Omar, Mohd Faizal Mohd Bakeri, Noorhadila Mohd Nawi, Mohd Nasrun Hairani, Norfazlirda Khalid, Khalizul |
| author_sort | Omar, Mohd Faizal |
| collection | UUM |
| description | Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectives and huge request from n users. The
current constraints surely limit for solving and optimizing the quality of Demand Side Management (DSM) case, such as the energy consumption of indoor comfort index parameters which consist of thermal comfort, air quality, humidity and vision comfort.To address these issues, this proposed work will firstly justify and validate the
constraints related to the appliances scheduling problem, and later proposes a new model of the Cluster based Multi-Objective WOA with multiple restart strategy. In order to achieve the objectives, different initialization strategy and cluster-based approaches will be used for tuning the main parameter of WOA under different
MapReduce application which helps to control exploration and exploitation, and the proposed model will be tested on a set of well-known test functions and finally, will be applied on a real case project i.e. appliances scheduling problem. It is anticipating that the approach can expedite the convergence of meta-heuristic technique with quality solution. |
| first_indexed | 2024-07-04T06:36:25Z |
| format | Article |
| id | uum-27814 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:36:25Z |
| publishDate | 2020 |
| publisher | Penerbit Akademia Baru |
| record_format | eprints |
| spelling | uum-278142020-11-01T01:54:47Z https://repo.uum.edu.my/id/eprint/27814/ Methodology for modified whale optimization algorithm for solving appliances scheduling problem Omar, Mohd Faizal Mohd Bakeri, Noorhadila Mohd Nawi, Mohd Nasrun Hairani, Norfazlirda Khalid, Khalizul QA76 Computer software Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectives and huge request from n users. The current constraints surely limit for solving and optimizing the quality of Demand Side Management (DSM) case, such as the energy consumption of indoor comfort index parameters which consist of thermal comfort, air quality, humidity and vision comfort.To address these issues, this proposed work will firstly justify and validate the constraints related to the appliances scheduling problem, and later proposes a new model of the Cluster based Multi-Objective WOA with multiple restart strategy. In order to achieve the objectives, different initialization strategy and cluster-based approaches will be used for tuning the main parameter of WOA under different MapReduce application which helps to control exploration and exploitation, and the proposed model will be tested on a set of well-known test functions and finally, will be applied on a real case project i.e. appliances scheduling problem. It is anticipating that the approach can expedite the convergence of meta-heuristic technique with quality solution. Penerbit Akademia Baru 2020 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/27814/1/JARFMTS%2076%202%202020%20132%20143.pdf Omar, Mohd Faizal and Mohd Bakeri, Noorhadila and Mohd Nawi, Mohd Nasrun and Hairani, Norfazlirda and Khalid, Khalizul (2020) Methodology for modified whale optimization algorithm for solving appliances scheduling problem. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 76 (2). pp. 132-143. ISSN 22897879 http://doi.org/10.37934/arfmts.76.2.132143 doi:10.37934/arfmts.76.2.132143 doi:10.37934/arfmts.76.2.132143 |
| spellingShingle | QA76 Computer software Omar, Mohd Faizal Mohd Bakeri, Noorhadila Mohd Nawi, Mohd Nasrun Hairani, Norfazlirda Khalid, Khalizul Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title | Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title_full | Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title_fullStr | Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title_full_unstemmed | Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title_short | Methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| title_sort | methodology for modified whale optimization algorithm for solving appliances scheduling problem |
| topic | QA76 Computer software |
| url | https://repo.uum.edu.my/id/eprint/27814/1/JARFMTS%2076%202%202020%20132%20143.pdf |
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