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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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Asian Research Publishing Network (ARPN)
2017
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/3616/1/AJ%202017%20%28501%29.pdf http://eprints.uthm.edu.my/3616/ |
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| Summary: | 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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