摘要
根据多目标进化算法思想,提出了无线传感器网络中多基站定位的多目标蚁群算法.该算法用一组蚂蚁并行搜索,用一个蚂蚁所在位置表示一个基站定位,多蚂蚁位置的组合表示多基站的定位.计算单基站和多基站定位的适应度,再根据这两个适应度值调整蚂蚁觅食路径上的信息素,蚂蚁沿着信息素强的方向搜索,不断逼近多目标优化的Parote解,从而获得全局优化的多基站定位解.实验结果表明,该算法求得的多基站定位位置能有效提高网络性能,且适用性强.
The multi-base station placement in a sensor network affects the universality performance of net directly. The problem of base station placement is known to be NP-hard. A multi-objective ant algorithm was presented for multi-base station placement based on evolutionary multi-objective optimization. In this algorithm, a group of ants search for base station placement in net simultaneously. The position of one ant denotes one base station placement, the combination position of many ants denotes multi-base station placement. The fitness of one base station placement and the fitness of multi-base station placement are evaluated. The quantity of pheromone is adjusted based on these fitness. The ants search along the direction of strong pheromone and converge toward the Pareto optimal solutions. Thus the optimal multi-base station placement is obtained. The proposed algorithm was validated by several experiments. The results show that the approach is effective and efficient. And the applicability of this algorithm is strong.
出处
《上海交通大学学报》
EI
CAS
CSCD
北大核心
2009年第3期449-454,共6页
Journal of Shanghai Jiaotong University
基金
国家自然科学基金资助项目(60673102)
江苏省自然科学基金资助项目(BK2006218)
关键词
传感器
基站定位
多目标优化
蚂蚁算法
sensor
base station placement
multi-objective optimization
ant algorithm
