摘要
航线网络是航空公司生产运营的基础,对公司的发展具有战略意义,通过优化设计方法构建一个符合公司实际并且鲁棒性强的网络将显得尤为重要。航线网络的优化理论一般是对既定结构的网络作抽象后建立的,对航线网络的规划指导具有一定的局限性。从系统复杂性的角度来分析网络的演化机制及运行特性对网络规划指导也具有重要意义。本文结合经济学理论、运筹学理论、经典算法和智能算法、统计学理论、复杂网络理论等对航线网络鲁棒优化设计及其复杂性问题进行研究。
OD间的客流量、单位流成本及节点的容量都具有很大的不确定性。这些不确定性因素将可能导致现有的网络结构与实际所需求的网络结构之间存在偏差,会对以网络为基础的生产带来很大影响,因此需要设计的航线网络具有较好的鲁棒性。本文以航空公司的客流量、单位流运输成本及容量数据为基础,建立离散型的情景集,在有容量限制的条件下进行枢纽航线网络鲁棒优化设计,并利用Benders分解算法进行求解。考虑到离散型的情景集包含的情景有限,本文定义区间型的情景集,建立了无容量限制的区间型绝对鲁棒优化设计模型和相对鲁棒优化设计模型,将修正最短路算法和模拟退火算法相结合进行求解,并以经典CAB数据和航空公司实际数据对模型进行实例分析。结果表明采用区间型鲁棒优化模型设计的网络有更强的鲁棒性,并且确定情形的优化模型只是该模型的特殊情形。
航线网络优化设计是在既定结构下进行的,因此对航线网络结构进行分析,对于选择特性优良的网络结构具有重要意义。本文在节点或边具有容量限制条件下,建立了具有容量限制的加权网络演化模型,利用平均场理论进行求解,理论解析解及仿真试验结果表明,新建立的网络演化模型能更好地再现实际网络的结构特征,经典BBV模型只是该模型当节点容量趋于无穷大时的特殊情形。网络生成之后,再对网络的运行特性进行分析。利用具有容量限制的演化网络模型,生成了有容量限制和无容量限制的演化网络,对比分析了这两种网络的网络容量、节点和边的中心-处理能力。本文还用预期流模型,生成了中国航线演化网络,并建立网络延误传播模型,从宏观上分析延误在不同参数、不同度值节点处时给网络带来的影响,包括受延误影响的节点总数、传播的距离等。在机场或航空公司的恢复策略下,延误现象一般不会导致网络的严重故障,文中还探讨了网络节点或边出现严重故障时,故障边的边权分配策略。级联失效过程仿真结果表明采用适当的分配策略,可使得网络的级联效应减弱或避免。
Airline network is a foundation for airlines’ operations and is strategic to the development ofairlines. It is important to build an airline network which is matching the realistic of the airlines and isrobust by means of optimization designing after analyzing the situation of airlines in current and aperiod in future. The optimization theory of airline network is generally aiming at the network whichis abstracted and has special structure. It has some limitations when guiding the planning anddesigning of airline network. It is also important to explore the evolution mechanism of network andoperation characteristics on network from the aspect of system complexity analysis. This paper willfocuse on on the robust optimization of airline network design and complexity analysis with the helpof economic theory, operations research theory, classic and intelligence algorithms, statistical theory,theory of complex networks and etc.
With the changes of the market environment, the traffic between the OD, unit transport costs andthe capacity of a node will have much uncertainty. These uncertainty factors will probably lead to adeviation between the existing network structure and the actual needing network structure, and willhave a great impact on the production based on the network, therefore there needs to make thedesigning network have better robustness. By analyzing the data of airline passenger traffic, unit flowtransport cost and nodes’ capacity, this paper defines a discrete scenario set, establishes a robustoptimization design model of Hub and spoke network under the capacity-limited conditions, and solvethe model with the Benders Decomposition algorithm. As the number of scenarios is limited in thediscrete scenario set, in order to analyze the problem in more wide and more complex environment,this paper defines an interval type of scenario set which contains more information, establishes twonetwork design models of uncapacitated interval absolute robust optimization and relative robustoptimization, solves the modes with the methods combining the modified shortest path algorithm andsimulation annealing algorithm, carries out some applications for the models using the classic CABdata and airlines actual data. The results show that the network designed by the models of the intervalrobust optimization has better robustness and the optimization model under the determinedcircumstances is a special case of the interval robust optimization model.
The optimization design of airline network is carried out under the special structure,so theanalysis of the structure of airline network will be important to select the excellence structure.Under the conditions of node or edge having capacity limit, this paper establishes a network evolution modelwith limited capacity, solves the model with mean field theory. The theoretical solutions andsimulation results indicate that the new model can better reappear some characteristics of actualnetworks and the BBV model is just a special case of the new model when the nodes’ capacity tendesto infinity. After the network is generated, its operation characteristics need to be analyzed. Using thenew evolution model, two types of network are genetated when the nodes’ capacity tendes to finity orinfinity, and then the capacity of the networks and center-deal ability of nodes and edges is caculatedand compared. Flights delay have impacted the air transport heavily, according to the model ofexpected flow, an evolution of Chinese airline network is generated, a delay spreading model iseastablished based on the network. After then, from the aspect of macro-level, considering differentcases, such as the parameters taking different values and the initial delay happening at node withdifferent degree, the delay influences are analyzed, including the whole number of delayed nodes andthe delay spreading distance and etc. Under the recovery strategy of airports or airlines, delayspreading usually does not cause serious influence on network, this paper also analyzes someallocation strategies of the weight of the unfuncitional edges when serious malfunctions happen.Simulation results indicate that the use of appropriate allocation strategies may reduce or avoide thecascading effect.
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