Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem

Philip de Bruin; Marjan van den Akker; Kunal Kumar; Lisanne Heuseveldt; Marc Paelinck

Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem

Philip de Bruin, Marjan van den Akker, Kunal Kumar, Lisanne Heuseveldt, Marc Paelinck

Sub Simulation of Complex Systems

KLM Royal Dutch Airlines

Research output: Contribution to conference › Abstract › Academic

Abstract

Airline operations are prone to delays and disruptions, in which case the resource or flight schedules need to be adjusted. Such adjustments need to resolve a disruption while minimizing costs and passenger impact. We look at resolving disruptions in both the aircraft and crew schedules, where we take an integrated approach. For this, we develop a fast local search algorithm that resolves these disruptions in a cost-efficient manner. This is done in collaboration with KLM Royal Dutch Airlines.

Original language	English
Publication status	Published - Jun 2024
Event	2024 AGIFORS Airline Operations Conference - Hamburg, Germany Duration: 10 Jun 2024 → 14 Jun 2024 https://www.agifors.org/ops-2024

Conference

Conference	2024 AGIFORS Airline Operations Conference
Country/Territory	Germany
City	Hamburg
Period	10/06/24 → 14/06/24
Internet address	https://www.agifors.org/ops-2024

1 Abstract
1 Preprint

Integrated Airline Fleet and Crew Recovery through Local Search
de Bruin, P., van den Akker, M., Kumar, K., Heuseveldt, L. & Paelinck, M., 7 May 2025, arXiv, 25 p. (Computers & Operations Research).
Research output: Working paper › Preprint › Academic

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Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem
de Bruin, P., van den Akker, M., Kumar, K., Heuseveldt, L. & Paelinck, M., Jul 2024.
Research output: Contribution to conference › Abstract › Academic

Cite this

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title = "Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem",

abstract = "Airline operations are prone to delays and disruptions, in which case the resource or flight schedules need to be adjusted. Such adjustments need to resolve a disruption while minimizing costs and passenger impact. We look at resolving disruptions in both the aircraft and crew schedules, where we take an integrated approach. For this, we develop a fast local search algorithm that resolves these disruptions in a cost-efficient manner. This is done in collaboration with KLM Royal Dutch Airlines.",

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T1 - Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem

AU - de Bruin, Philip

AU - van den Akker, Marjan

AU - Kumar, Kunal

AU - Heuseveldt, Lisanne

AU - Paelinck, Marc

PY - 2024/6

Y1 - 2024/6

N2 - Airline operations are prone to delays and disruptions, in which case the resource or flight schedules need to be adjusted. Such adjustments need to resolve a disruption while minimizing costs and passenger impact. We look at resolving disruptions in both the aircraft and crew schedules, where we take an integrated approach. For this, we develop a fast local search algorithm that resolves these disruptions in a cost-efficient manner. This is done in collaboration with KLM Royal Dutch Airlines.

AB - Airline operations are prone to delays and disruptions, in which case the resource or flight schedules need to be adjusted. Such adjustments need to resolve a disruption while minimizing costs and passenger impact. We look at resolving disruptions in both the aircraft and crew schedules, where we take an integrated approach. For this, we develop a fast local search algorithm that resolves these disruptions in a cost-efficient manner. This is done in collaboration with KLM Royal Dutch Airlines.

M3 - Abstract

T2 - 2024 AGIFORS Airline Operations Conference

Y2 - 10 June 2024 through 14 June 2024

ER -

Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem

Abstract

Conference

Fingerprint

Research output

Integrated Airline Fleet and Crew Recovery through Local Search

Simulated Annealing to Solve the Integrated Airline Fleet and Crew Recovery Problem

Cite this