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Wireless Heterogeneous Transmitter Placement Using Multiobjective Variable-Length Genetic Algorithm
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Wireless Heterogeneous Transmitter Placement Using Multiobjective Variable-Length Genetic Algorithm

Chuan-Kang Ting, Chung-Nan Lee, Hui-Chun ChangJain-Shing Wu
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 卷.39(4), 頁碼.945-958
2009
PMID: 19362914

摘要

Multiobjective (MO) optimization variablelength genetic algorithm wireless heterogeneous transmitter placement Control and Systems Engineering Software Medicine (all) Information Systems Human-Computer Interaction Computer Science Applications Electrical and Electronic Engineering
The problem of placing wireless transmitters to meet particular objectives, such as coverage and cost, has proven to be NP-hard. Furthermore, the heterogeneity of wireless networks makes the problem more intractable to deal with. This paper presents a novel multiobjective variable-length genetic algorithm to solve this problem. One does not need to determine the number of transmitters beforehand; the proposed algorithm simultaneously searches for the optimal number, types, and positions of heterogeneous transmitters by considering coverage, cost, capacity, and overlap. The proposed algorithm can achieve the optimal number of transmitters with coverage exceeding 98% on average for six benchmarks. These preferable experimental results demonstrate the high capability of the proposed algorithm for the wireless heterogeneous transmitter placement problem. © 2009, IEEE.

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