航班调度问题的不确定规划方法
发布时间：2018-12-08 10:35
【摘要】：不正常航班计划恢复是实时优化的过程。引起不正常航班的发生的原意非常多,其中主要包括:恶劣的天气、飞行器的故障、交通管制等。然而这些事件的发往往都是不可提前预知的,因此不正常航班的发生也是不可提前预知的,且其研究也是缺乏大量数据的。当这些突发事件发生时,用传统的确定性模型或随机条件下的规划模型是无法解决不正常航班恢复问题的,或者说是不可靠的。为了更好的处理这些不确定因素,本文引入了不确定规划。首先,对于飞机恢复问题,基于不确定理论,将航班延误时间作为不确定变量,以航班延误成本和旅客失望信度最小化为目标的双目标不确定规划模型。应用不确定理论,将该模型转化成确定性模型,并给出了新的最短路径算法解决该问题,通过实例证明了了该不确定规划模型及其求解算法的有效性与可靠性。其次,考虑机组恢复问题,同样以航空公司总的延误损失成本和旅客失望率最小化为目标,建立了机组配对问题的双目标不确定规划模型,依据不确定理论,将该不确定模型转化成确定型形式,并应用遗传算法解决该模型,通过实例的结果分析,表明了该模型及算法的有效性和实用性。
[Abstract]:Abnormal flight schedule recovery is a real-time optimization process. There are many reasons for abnormal flight, including bad weather, malfunction of aircraft, traffic control and so on. However, the occurrence of these events is often unpredictable, so the occurrence of abnormal flights is unpredictable, and its research is also lack of a lot of data. When these emergencies occur, the traditional deterministic model or the programming model under random conditions can not solve the problem of abnormal flight recovery, or it is unreliable. In order to deal with these uncertainties better, this paper introduces uncertain programming. Firstly, for aircraft recovery problem, based on uncertainty theory, flight delay time is taken as an uncertain variable, and a double-objective uncertain programming model with the goal of minimizing flight delay cost and passenger disappointment reliability is proposed. The uncertainty theory is applied to transform the model into a deterministic model, and a new shortest path algorithm is presented to solve the problem. The validity and reliability of the uncertain programming model and its algorithm are proved by an example. Secondly, considering the problem of crew recovery, taking the total cost of delay loss and the minimization of passenger disappointment rate as the goal, a two-objective uncertain programming model for the problem of crew matching is established, which is based on the theory of uncertainty. The uncertain model is transformed into a definite form, and the genetic algorithm is used to solve the model. The results of an example show the validity and practicability of the model and the algorithm.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O221
[Abstract]:Abnormal flight schedule recovery is a real-time optimization process. There are many reasons for abnormal flight, including bad weather, malfunction of aircraft, traffic control and so on. However, the occurrence of these events is often unpredictable, so the occurrence of abnormal flights is unpredictable, and its research is also lack of a lot of data. When these emergencies occur, the traditional deterministic model or the programming model under random conditions can not solve the problem of abnormal flight recovery, or it is unreliable. In order to deal with these uncertainties better, this paper introduces uncertain programming. Firstly, for aircraft recovery problem, based on uncertainty theory, flight delay time is taken as an uncertain variable, and a double-objective uncertain programming model with the goal of minimizing flight delay cost and passenger disappointment reliability is proposed. The uncertainty theory is applied to transform the model into a deterministic model, and a new shortest path algorithm is presented to solve the problem. The validity and reliability of the uncertain programming model and its algorithm are proved by an example. Secondly, considering the problem of crew recovery, taking the total cost of delay loss and the minimization of passenger disappointment rate as the goal, a two-objective uncertain programming model for the problem of crew matching is established, which is based on the theory of uncertainty. The uncertain model is transformed into a definite form, and the genetic algorithm is used to solve the model. The results of an example show the validity and practicability of the model and the algorithm.
【学位授予单位】：中国民航大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：O221
【参考文献】
相关期刊论文 前10条
1 乐美龙;张旭;;中小型航空公司多机型机组复原问题研究[J];武汉理工大学学报(信息与管理工程版);2014年01期
2 张英楠;牟德一;李辉;;基于机会约束规划的航班应急调度问题研究[J];中国安全科学学报;2012年12期
3 张涛;胡佳研;李福娟;张sソ，
本文编号：2368204
本文链接：https://www.wllwen.com/shoufeilunwen/benkebiyelunwen/2368204.html
