Presentation of a Robust Two-Step Optimization Model for Integrated Planning of Aircraft Net Routing and Crew Routing Under the Risk of Flight Disruption

Document Type : Scientific - Research

Authors

1 Ph.D. student, Department of Industries, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor, Department of Industries, Central Tehran Branch, Islamic Azad University, Tehran, Iran

3 Assistant professor, Department of Industries, Central Tehran Branch, Islamic Azad University, Tehran, Iran

4 Associate Professor, Higher Institute of Management and Planning Education and Research, Tehran, Iran

Abstract

After network and flight schedule design, routing and aircraft maintenance and repair issues as well as aircrew planning are among the major decisions that affect airline costs. When making decisions on each of these issues, there are specific operational restrictions and rules and regulations that must be followed. If these decisions are integrated and the optimal response is found, there will be a significant reduction in airline cost. In this research, assuming that an airline has designed the flight program at a strategic level, how to optimally implement this program is discussed; to this end, the optimal integration of aircraft routing decisions and the crew's movement plan (flight team) was considered. The desired problem for an airline is solved with net base and crew diversity, with the goal of minimizing total costs. One of the biggest challenges in solving this problem is the possible disruption of the original plan, which makes aircraft and crew planning ineffective in practice. Therefore, in this research, we define the possible disturbances in the initial plan as several different scenarios and by using the two-step robust scenario-oriented optimization approach, we provide a robust answer to the problem of integrating the decisions of aircraft network routing. And the crew's travel plan. In the proposed stable model, in addition to the decision integration, the adjustable variables of the second stage, including the decision to cancel the flight in the event of a disturbance, are also seen so that the model is adaptable to different disturbance scenarios. . The numerical results of the implementation of the proposed model confirm the applicability of the proposed model to provide an integrated and stable answer to the research problem.

Keywords

References

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History

  • Receive Date: 18 December 2021
  • Revise Date: 10 April 2022
  • Accept Date: 01 May 2022

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