Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning
The RFID network planning (RNP) problem belongs to the large-scale multi-objective hard optimization problems. RNP aims to optimize the overall read region based on a set of objectives. A novel approach of hybrid firefly algorithm was developed for multi-objective RNP problem. The technique was comb...
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Asian Research Publishing Network (ARPN)
2017
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my.uthm.eprints.36162021-11-21T03:37:50Z http://eprints.uthm.edu.my/3616/ Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning Elewe, Adel Muhsin Hasnan, Khalid Nawawi, Azli TK7800-8360 Electronics The RFID network planning (RNP) problem belongs to the large-scale multi-objective hard optimization problems. RNP aims to optimize the overall read region based on a set of objectives. A novel approach of hybrid firefly algorithm was developed for multi-objective RNP problem. The technique was combining the Density Based Clustering method (DBSCAN) and firefly algorithm. Empirical tests were conducted on six standard RFID benchmark sets with random and clustered topologies. A comparative analysis performed with other state-of-the-art algorithms based on the same test data.Simulation results exhibited uniformly better performance in achieving maximum coverage with smaller number of deployed readers and less transmitted power. Asian Research Publishing Network (ARPN) 2017-02 Article PeerReviewed text en http://eprints.uthm.edu.my/3616/1/AJ%202017%20%28501%29.pdf Elewe, Adel Muhsin and Hasnan, Khalid and Nawawi, Azli (2017) Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning. ARPN Journal of Engineering and Applied Sciences, 12 (3). pp. 834-840. ISSN 1819-6608 |
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TK7800-8360 Electronics Elewe, Adel Muhsin Hasnan, Khalid Nawawi, Azli Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
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The RFID network planning (RNP) problem belongs to the large-scale multi-objective hard optimization problems. RNP aims to optimize the overall read region based on a set of objectives. A novel approach of hybrid firefly algorithm was developed for multi-objective RNP problem. The technique was combining the Density Based Clustering method (DBSCAN) and firefly algorithm. Empirical tests were conducted on six standard RFID benchmark sets with random and clustered topologies. A comparative analysis performed with other state-of-the-art algorithms based on the same test data.Simulation results exhibited uniformly better performance in achieving maximum coverage with smaller number of deployed readers and less transmitted power. |
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Article |
author |
Elewe, Adel Muhsin Hasnan, Khalid Nawawi, Azli |
author_facet |
Elewe, Adel Muhsin Hasnan, Khalid Nawawi, Azli |
author_sort |
Elewe, Adel Muhsin |
title |
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
title_short |
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
title_full |
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
title_fullStr |
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
title_full_unstemmed |
Hybridized firefly algorithm for multi-objective radio frequency identification (RFID) network planning |
title_sort |
hybridized firefly algorithm for multi-objective radio frequency identification (rfid) network planning |
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Asian Research Publishing Network (ARPN) |
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2017 |
url |
http://eprints.uthm.edu.my/3616/1/AJ%202017%20%28501%29.pdf http://eprints.uthm.edu.my/3616/ |
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1738581146162167808 |
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13.159267 |