Wireless heterogeneous transmitter placement using multiobjective variable-length genetic algorithm.
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.
Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi 621, Taiwan. ckting@cs.ccu.edu.tw
Chuan-Kang
CK
Ting
Chung-Nan
CN
Lee
Hui-Chun
HC
Chang
Jain-Shing
JS
Wu
D000465:Algorithms; D003195:Computer Communication Networks; D003198:Computer Simulation; D003491:Cybernetics / Q000379:methods*; D004581:Electronics / Q000379:methods; D020407:Internet; D008957:Models, Genetic