航班快速恢复建模与仿真研究

随着民用航空的发展与竞争,航班延误不仅影响航空飞行的安全与正常,更与航空公司的运营效率、运营成本及乘客利益息息相关。针对某一恶劣天气影响,对某公司受影响航班进行重新调配,考虑到航班的备降、盘旋等待、延误、取消等多种状态,以总成本最小为目标函数,建立航班快速恢复模型,通过MATLAB运用遗传算法设计航班恢复算法进行求解,得出最经济的航班恢复方案。     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

基于绿色飞行的航空器离场累积事件噪声控制研究

航空业的迅猛发展,在带来巨大经济、社会效益的同时,也造成日益严重的噪声污染.为缓解机场周边噪声问题,贯彻"绿色飞行"理念,本文从飞行程序优化和飞行架次调整两方面进行航空器离场噪声控制研究.采用计权等效连续感觉噪声级为评价指标,应用累积事件噪声计算模型,以广州白云机场为例,绘制噪声等值线图,计算噪声影响面积,分析噪声控制效果及原因.结果表明,CCO减噪程序和飞行架次调整两种方法均可有效减少噪声影响面积,但噪声控制方法各有利弊,实践过程中应扬长避短灵活运用.     

Fueling for contingencies: The hidden cost of unpredictability in the air transportation system

The aviation community is increasing its attention on the concept of predictability when conducting aviation service quality assessments. Reduced fuel consumption and the related cost is one of the various benefits that could be achieved through improved flight predictability. A lack of predictability may cause airline dispatchers to load more fuel onto aircraft before they depart; the flights would then in turn consume extra fuel just to carry excess fuel loaded. In this study, we employ a large dataset with flight-level fuel loading and consumption information from a major US airline. With these data, we estimate the relationship between the amount of loaded fuel and flight predictability performance using a statistical model. The impact of loaded fuel is translated into fuel consumption and, ultimately, fuel cost and environmental impact for US domestic operations. We find that a one-minute increase in the standard deviation of airborne time leads to a 0.88 min increase in loaded contingency fuel and 1.66 min in loaded contingency and alternate fuel. If there were no unpredictability in the aviation system, captured in our model by eliminating standard deviation in flight time, the reduction in the loaded fuel would between 6.12 and 11.28 min per flight. Given a range of fuel prices, this ultimately would translate into cost savings for US domestic airlines on the order of $120–$452 million per year.     

航班延误成本测算方法研究

针对目前对航班延误成本没有一个很明确的测算方法,通过研究国内航空公司的管理运行模式,作者重新划分了航空公司的延误成本结构,并据此提出了一种新的测算航班延误成本分析模型.按照该模型对B737-800与A320-200这两种国内航空公司的主流机型的延误成本进行了比较与计算,其结果可以为相关的管理决策提供有利的参考.该模型可...     

基于灰色二次指数平滑的QAR参数关联度预测

由于QAR参数波动的后果具有潜在性和滞后性,因此分析人员容易忽视其危险性而使其发展为不利事件。针对该问题,提出运用QAR参数关联度分析的方法,建立QAR参数波动与事件之间的对应关系;并构建基于二次指数平滑-灰色关联法的关联度预测模型,进一步明确QAR参数波动与事件之间关系的动态变化趋势。运用实际数据对该模型进行验证,表明结论符合实际,该模型科学合理,可以用于QAR参数分析过程。     

Weekly Fleet Assignment Model and Algorithm

A 0-1 integer programming model for weekly fleet assignment was put forward based on linear network and weekly flight scheduling in China. In this model, the objective function is to maximize the total profit of fleet assignment, subject to the constraints of coverage, aircraft flow balance, fleet size, aircraft availability, aircraft usage, flight restriction, aircraft seat capacity, and stopover. Then the branch-and-bound algorithm based on special ordered set was applied to solve the model. At last, a real-world case study on an airline with 5 fleets, 48 aircrafts and 1786 flight legs indicated that the profit increase was $1591276 one week and the running time was no more than 4 min, which shows that the model and algorithm are fairly good for domestic airline.     

Effects of noise exposure of other people on aircraft noise tolerability using a reference point approach

Reactions to aircraft noise resulting from an airport development vary considerably among individuals. This paper examines whether the noise level tolerated by individuals is affected when they compare their own situation to the situations of other people who are more severely affected by the noise. We modeled the individual noise tolerability by adopting the reference point concept and the value function of prospect theory. A questionnaire assessed different levels of noise-affected zones at a hypothetical airport. Individual noise tolerable level was measured by a prerecorded aircraft noise presented via headphones. Decision-making associated with the reported satisfaction level regarding the changes in operational flight frequency settings at the airport. An interview survey was conducted with residents near Manila airport in the Philippines. We applied genetic algorithm to jointly estimate the parameters for noise tolerability model and the value function. Results showed that individuals tolerated more overhead flights when they considered the situations of other people worse affected by the noise than they were. The tendency of noise tolerability increased with the severity of noise exposure situations of other people, but lower reactions to noise escalation. We also observed diminishing sensitivity to changes in noise relative to the noise tolerable level. The aircraft noise tolerability and the consideration of noise exposure situations of other people appeared to be a vital aspect to be considered in airport noise management and policy.     

‘Each flight is different’: Carbon emissions of selected flights in three geographical markets

Air travel is considered the biggest individual climate sin. Avoiding flying, however, seems impossible. In this paper we argue that the flight a passenger chooses can be significant. For this purpose we compared the carbon emissions of selected flights in three geographical markets. We found tremendous differences in the environmental performance of individual flights. Furthermore, we also found that flying with the most modern aircraft or flying non-stop represents, in many cases, the least polluting option. Nevertheless, we were able to show that there are exceptions to this rule. Based on our results, we provide recommendations to the industry and for further research.