Developing a Model for Solving the Flight Perturbation Problem

Journal of Airline and Airport Management

Amirreza Nickkar¹  Seyedmohammad Seyed-Hosseini²  Hassan Javanshir¹  Hasan Khaksar² 

[1] Azad University of Tehran (South Branch);University of Science & Technology of Iran

关键词: Flight perturbation problem;    disruption management;    rescheduling;    optimization;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: Universitat Politecnica de Catalunya

【 摘 要 】

Purpose : In the aviation and airline industry, crew costs are the second largest direct operating cost next to the fuel costs. But unlike the fuel costs, a considerable portion of the crew costs can be saved through optimized utilization of the internal resources of an airline company. Therefore, solving the flight perturbation scheduling problem, in order to provide an optimized schedule in a comprehensive manner that covered all problem dimensions simultaneously, is very important. In this paper, we defined an integrated recovery model as that which is able to recover aircraft and crew dimensions simultaneously in order to produce more economical solutions and create fewer incompatibilities between the decisions.Design/methodology/approach : Current research is performed based on the development of one of the flight rescheduling models with disruption management approach wherein two solution strategies for flight perturbation problem are presented: Dantzig-Wolfe decomposition and Lagrangian heuristic.Findings : According to the results of this research, Lagrangian heuristic approach for the DW-MP solved the problem optimally in all known cases. Also, this strategy based on the Dantig-Wolfe decomposition manage to produce a solution within an acceptable time (Under 1 Sec).Originality/value : This model will support the decisions of the flight controllers in the operation centers for the airlines. When the flight network faces a problem the flight controllers achieve a set of ranked answers using this model thus, applying crew’s conditions in the proposed model caused this model to be closer to actual conditions.

【 授权许可】

Unknown