计算机与现代化

• 算法设计与分析 •    下一篇

航班恢复问题的迭代局部搜索算法

  

  1. (1.北京交通大学计算机与信息技术学院,北京100044;2.交通数据分析与挖掘北京市重点实验室,北京100044)
  • 收稿日期:2019-02-28 出版日期:2019-09-23 发布日期:2019-09-23
  • 作者简介:肖晚霞(1993-),女,江西九江人,硕士研究生,研究方向:智能优化算法,组合优化,E-mail: 18800103523@163.com; 董兴业(1974-),男,河南漯河人,副教授,研究方向:调度理论和算法,组合优化算法; 林友芳(1971-),男,福建武平人,教授,研究方向:数据与知识工程,E-mail: yflin@bjtu.edu.cn。
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(2017JBM027)

An Iterated Local Search Algorithm  for Aircraft Recovery Problem

  1. (1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
    2. Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing 100044, China)
  • Received:2019-02-28 Online:2019-09-23 Published:2019-09-23

摘要: 在恶劣天气和机械故障等原因造成航班不能按照原计划执行时,航空公司需要采取相应的措施对航班进行恢复。本文基于经典的资源指派模型,综合考虑了调整时间、换机、联程拉直、取消航班和调机5种恢复策略,提出一种以最小化加权成本为优化目标的航班恢复模型,并设计一种迭代局部搜索算法。首先用构造-修复启发式方法构造可行解,然后从该初始解出发,在飞机路线对的邻域中进行局部搜索。当陷入局部最优后,对解进行扰动,然后从扰动后的解重新出发进行局部搜索。为了提高搜索效率,同时降低陷入局部最优解的概率,局部搜索过程采用模拟退火算法。实例结果表明,本文提出的模型及算法能够在短时间内对受到影响的大规模航班计划进行恢复。

关键词: 航班恢复问题, 迭代局部搜索, 模拟退火, 联程航班, 飞机路线

Abstract:  Airlines are required to take corresponding measures to recover the flights when they cannot be implemented as original plan due to certain disturbations. This paper puts forward a flight recovery model based on the classical resource assignment model, taking into account five recovery strategies, i.e adjusting time, changing aircraft, adjusting connecting flight, cancelling flight and deadhead flight. The model minimizes total weighted cost and an iterative local search algorithm is designed. Firstly, the feasible solution is constructed by construct-repair heuristic method, and then the local search is carried out from it in a multi-neighborhood of the aircraft route. When the search is trapped into a local optimum, the current solution is disturbed, and then the local search is performed again from the disturbed solution. To accelerate the local search and reduce the probability of falling into the local optimal, a simulated annealing algorithm is used. Experimental results demonstrate that the proposed model and algorithm can recover the large-scale flight schedule that is affected in a short time.

Key words: flight recovery problem, iterated local search, simulated annealing, connecting flight, aircraft route

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