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摘要: 为了使枢纽辐射式航线网络能够适应不确定的交通需求, 分析了航空运输需求不确定的影响因素及长短距离交通需求分布特性, 提出需求不确定有容量限制的枢纽辐射式航线网络设计模型, 并将其转化为机会约束规划模型, 采用基于随机模拟的遗传算法对模型进行求解。以包含15个城市的中国航线网络规划为例, 进行了需求不确定情况下的枢纽辐射式航线网络设计。研究结果表明: 在合理的枢纽数量范围内, 需求确定与不确定的枢纽辐射式航线网络选址结果基本相同, 但与长距离交通出行相比, 短距离路径选择变化较大; 需求不确定的枢纽辐射式网络最小运输成本较低, 并更能真实地反映网络性能。Abstract: In order to adapt to uncertainty demand for hub-and-spoke airline network, the influence factors and distribution characteristics of long-distance and short-distance traffic demands were analyzed.A stochastic and capacitated hub-and-spoke airline network design model was proposed.The model was transformed into chance-constrained programming model and solved by stochastic simulation-based genetic algorithm.Taking 15 cities of Chinese airline network planning as an example, hub-and-spoke network design with uncertainty demand was analyzed.Analysis result indicates that hub locations with certainty and uncertainty demands are almost same in the reasonable range of hub numbers, but compared with long-distance traffic demand, the route choice of short-distance demand changes greatly.The hub-and-spoke airline network with uncertainty demand has lower minimum transportation cost, and can better reflect true network performance.
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表 1 枢纽选址及最小运输成本
Table 1. Hub locations and minimum transportation costs
枢纽数量p 需求确定有容量限制 需求不确定有容量限制 枢纽点 最小运输成本/ (亿元·年-1) 成本变化率/% 枢纽点 最小运输成本/ (亿元·年-1) 成本变化率/% 1 北京 1 825 北京 1 787 2 北京、上海 1 498 -17.62 北京、广州 1 460 -18.30 3 北京、广州、上海 1 267 -15.42 北京、广州、上海 1 239 -15.14 4 北京、成都、广州、上海 1 127 -11.05 北京、成都、广州、上海 1 124 -9.28 5 北京、成都、广州、昆明、上海 1 057 -6.21 北京、成都、广州、上海、西安 1 051 -6.49 
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