A constraint programming model and a hybrid iterated local search algorithm for solving an aircraft recovery problem in the oil and gas industry

Mateus Martin, Aldair Alvarez, Jonathan De La Vega and Reinaldo Morabito

Journal of the Operational Research Society, 2025, vol. 76, issue 12, 2494-2506

Abstract: In this paper, we address a challenging problem faced by a Brazilian oil and gas company regarding the rescheduling of helicopter flights from an onshore airport to maritime units, crucial for transporting company employees. The problem arises due to unforeseen events like bad weather or mechanical failures, leading to delays or postponements in the original flight schedules, disrupting the operation of maritime units, and employee shift scheduling. To model and solve the problem, we propose a constraint programming (CP) model aimed at optimizing daily flight scheduling with minimal delay and helicopter usage, considering various constraints like rescheduling priorities and time windows. We also develop a hybrid iterated local search algorithm to handle larger instances of the problem for the case when a general-purpose CP solver may not be available. Our approaches, evaluated using real-world data, demonstrate their effectiveness in solving short-term flight rescheduling problems in the context of the oil and gas industry, in comparison to exact and heuristic approaches from the literature.

Date: 2025
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DOI: 10.1080/01605682.2025.2478257

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