Abstract
In this paper, a new genetic algorithm with elite mutation is proposed for optimization problems. The proposed elite mutation scheme (EM) improves traditional genetic algorithms with a better ability to locate and to approach fast to optimal solutions, even in cases of huge data set. The proposed EM is to select elite chromosomes and mutate according to the similarity between elite chromosomes and selected chromosomes. The designed similarity guides effectively the search toward optimal solutions with less generation. The proposed EM is applied to optimize the cruise area of mobile sinks in hierarchical wireless sensor networks (WSNs). Numeric results show that (1) the proposed EM benefits the discovery of optimal solutions in a large solution space; (2) the approach to optimal solutions is more stable and faster; (3) the search guidance derived from the chromosome similarity is critical to the improvements of optimal solution discovery. Besides, the minimization of cruise are been proved to have the advantages of energy-saving, time-saving and reliable data collection in WSNs.
Original language | English |
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Pages | 402-412 |
Number of pages | 11 |
DOIs | |
Publication status | Published - 17 Dec 2012 |
Event | The 4th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI) - Duration: 28 Nov 2012 → … |
Conference
Conference | The 4th International Conference on Computational Collective Intelligence Technologies and Applications (ICCCI) |
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Period | 28/11/12 → … |
Keywords
- Cruise area optimization
- Elite mutation
- Genetic algorithm
- Hierarchical wireless sensor networks
- Mobile data sinks