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Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval 认领 引用 被引量：9
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作者 Zhang Xuejun Guan Xiangmin +1 位作者 Zhu Yanbo Lei Jiaxing 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2015年第2期556-563,共8页
The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategi... The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by rea- sonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimiza- tion problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm （MPEA） framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is pro- posed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution （CC） algorithm combined with non-dominated sorting genetic algorithm II （NSGA-II） is intro- duced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi- objective genetic algorithm （MOGA）, multi-objective evolutionary algorithm based on decom- position （MOEA/D）, CC-based multi-objective algorithm （CCMA） as well as other two MPEAs with different migration interval strategies. 展开更多
关键词 Air traffic flow management Cooperative co-evolution Dynamic migration intervalstrategy Flight assignment Parallel evolution algorithm
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一种基于并行搜索策略的苍狼算法 认领 引用 被引量：3
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作者 符强 汪鹏君 童楠 《计算机应用研究》 CSCD 北大核心 2016年第6期1662-1665,共4页
作为一种新型群体智能方法,苍狼算法模拟了苍狼在群体捕食过程中的搜索跟踪、包围、攻击等行为,具有结构简单、寻优能力强的特点。分析了该算法的优化机理,并对算法优化过程进行了数学定义及描述;提出了一种基于并行搜索策略的改进型苍... 作为一种新型群体智能方法,苍狼算法模拟了苍狼在群体捕食过程中的搜索跟踪、包围、攻击等行为,具有结构简单、寻优能力强的特点。分析了该算法的优化机理,并对算法优化过程进行了数学定义及描述;提出了一种基于并行搜索策略的改进型苍狼算法,将狼群分组,在整个搜索过程中同时进行局部开发和全局探索活动,以更好地满足目标搜寻的要求。通过典型的基准测试函数对算法进行了性能仿真测试,实验结果表明,与其他群体智能优化方法相比,改进型苍狼算法在收敛速度、收敛精度及鲁棒性等方面均具有一定优势。 展开更多
关键词 苍狼算法 群体智能 并行搜索策略 仿生机制 函数优化
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