期刊
COMPUTING
卷 103, 期 7, 页码 1439-1460出版社
SPRINGER WIEN
DOI: 10.1007/s00607-021-00906-0
关键词
Artificial bee colony algorithm; Teaching strategy; Wireless sensor network; Coverage optimization
资金
- Talent Introduction Foundation of Chengdu University of Information Technology [376148]
This paper proposes a wireless sensor network coverage optimization method based on an improved artificial bee colony (ABC) algorithm, which combines the strong global search ability of ABC with the rapid convergence ability of TLBO, maintaining diversity and eliminating parameter limits.
Considering the complexity of wireless sensor network (WSN) coverage problems, which include many variables and a large continuous search space, a WSN coverage optimization method based on an improved artificial bee colony (ABC) algorithm with teaching strategy is proposed in this paper. ABC, which is good at exploration but poor at exploitation, is improved by introducing a teaching strategy in teaching-learning-based optimization (TLBO) that has a rapid convergence but is easily trapped in a local optima. Thus, the proposed algorithm combines the advantages of ABC strong global search ability and TLBO rapid convergence. In addition, to retain the diversity and eliminate the parameter limit in ABC, a dynamic search update strategy is introduced instead of the scout bee phase of ABC. In addition to preliminary examinations with a number of benchmark functions, the performance of the algorithm is verified by solving a complicated wireless sensor network coverage problem. The simulation results verify that the proposed algorithm achieves better balance between global and local search compared with other state-of-the-art algorithms.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据