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基于偏好排序淘汰NSGAII算法的短波网络多区域重点覆盖优化方法

李新超 贺前华 李艳雄 朱铮宇

李新超, 贺前华, 李艳雄, 朱铮宇. 基于偏好排序淘汰NSGAII算法的短波网络多区域重点覆盖优化方法[J]. 电子与信息学报, 2017, 39(8): 1779-1787. doi: 10.11999/JEIT161172
引用本文: 李新超, 贺前华, 李艳雄, 朱铮宇. 基于偏好排序淘汰NSGAII算法的短波网络多区域重点覆盖优化方法[J]. 电子与信息学报, 2017, 39(8): 1779-1787. doi: 10.11999/JEIT161172
LI Xinchao, HE Qianhua, LI Yanxiong, ZHU Zhengyu. Multi-areas Outstanding Covering Optimization Method of HF Network Based on Preference Ranking Elimination NSGAII Algorithm[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1779-1787. doi: 10.11999/JEIT161172
Citation: LI Xinchao, HE Qianhua, LI Yanxiong, ZHU Zhengyu. Multi-areas Outstanding Covering Optimization Method of HF Network Based on Preference Ranking Elimination NSGAII Algorithm[J]. Journal of Electronics & Information Technology, 2017, 39(8): 1779-1787. doi: 10.11999/JEIT161172

基于偏好排序淘汰NSGAII算法的短波网络多区域重点覆盖优化方法

doi: 10.11999/JEIT161172
基金项目: 

国家自然科学基金(61571192),广东省公益研究(2015A010103003)

Multi-areas Outstanding Covering Optimization Method of HF Network Based on Preference Ranking Elimination NSGAII Algorithm

Funds: 

The National Natural Science Foundation of China (61571192), The Public Welfare Research Project of Guangdong Province (2015A010103003)

  • 摘要: 在采用偏好NSGAII算法求解多子区域重点覆盖的短波网络频率优化指配时,针对算法中非支配排序耗时较多的问题,该文提出一种偏好排序淘汰的NSGAII算法。在进行非支配排序前,根据解的偏好评价排序结果淘汰一部分偏好评价较差的解,减少参与非支配排序的解的数量从而减少求解时间,同时降低偏好评价结果较差的个体解被选中进行交叉、变异的概率,提高算法的求解效率和求解效果。在进行的48组数据测试中,该文算法在其中38组决策解偏好评价结果和求解时间同时最优,相同迭代次数时相比偏好NSGAII算法节省27%的求解时间。结果表明通过偏好排序淘汰机制的引入,更好利用了偏好信息,使算法用较少的时间求得更好的偏好解。
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出版历程
  • 收稿日期:  2016-11-02
  • 修回日期:  2017-03-01
  • 刊出日期:  2017-08-19

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