期刊文献+

航路流量间隔限制及排序策略一体化决策模型及算法 被引量:8

Integrative decision making model and solution algorithm for en route flow spacing restriction and sequencing strategy
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摘要 基于流量间隔限制策略和航路排序策略之间的关联性建立了两种策略一体化决策的二层双目标规划模型.模型将间隔限制值作为上层规划的决策变量,将排序相关变量作为下层规划的决策变量,在上层规划中同时考虑下级的目标函数.对模型设计了基于NSGA-II的多目标遗传算法求解,采用了一个快速启发式算法求解下层规划的单目标问题.结合中南区域实际空域及流量数据对模型进行了验证,并与当前实际运行中的按交通需求比率分配方法进行了比较.结果表明所建立的二层双目标规划模型能满足一体化决策的需求,所采用的算法能求得多个Pareto近似最优前沿解以供决策选择. A bi-objective bi-level programming model was established for the integrative decision making of en route flow spacing restriction and sequencing strategy based on the relationship between the two strategies. The decision variable in the upper level was the spacing value and decision variable in the lower level was the sequencing related variable. The upper level programming took into account the objective in the lower level. A method to solve the model based on NSGA-II multi-objective genetic algorithm was designed. The single objective programming in the lower level was solved with a fast heuristic algorithm. The model was verified with the practical airspace and air traffic data from the Middle South Area and compared with the proportional distribution method according to traffic demand ratio. The results indicates that the bi-objective bi-level programming model can meet the integrative decision making demand and the algorithm is capable of finding multi-Pareto optimal front for decision choice.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2013年第9期2430-2436,共7页 Systems Engineering-Theory & Practice
基金 国家科技支撑计划重大项目(2011BAH24B09) 中央高校基本科研业务费科研基地创新资金(NJ20130001)
关键词 间隔限制 航路排序 二层规划模型 NSGA-Ⅱ多目标遗传算法 spacing restriction en route sequencing bi-level programming models NSGA-II multi-objective genetic algorithm
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参考文献10

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