Heuristics for flight and maintenance planning of mission aircraft

Kozanidis, George; Gavranis, Andreas; Liberopoulos, George

doi:10.1007/s10479-013-1376-6

Cited by 14 publications

(4 citation statements)

References 10 publications

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“…Kozandis [13] proposed a flight and maintenance planning problem for a military fleet with the aim of maximizing the fleet availability and minimizing the total residual flight time. Kozanidis et al [14] presented a heuristic approach to solve flight and maintenance planning of mission aircraft with the aim of maximum fleet availability over a given planning horizon, while also satisfying certain flight and maintenance requirements.…”

Section: Literature Reviewmentioning

confidence: 99%

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Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

2021

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We study the maintenance task scheduling problem for an aircraft fleet in an uncertain environment from the viewpoint of robust optimization. Given a daily horizon, the maintenance tasks delegated to a shop should be scheduled in such a way that sufficient aircrafts are available on time to meet the demand of planned missions. The tasks are either scheduled maintenance activities or unexpected repair jobs when a major fault is detected during pre-or after-flight check of each mission. The availability of skilled labour in the shop is the main constraint. We propose a robust formulation so that the maintenance tasks duration is subject to unstructured uncertainty due to the environmental and human factors. As a result of the specific structure of the primary model and non-convexity of the feasible space, the classical robust optimization methods cannot be applied. Thus, we propose an ϵ-Conservative model in tandem with Monte-Carlo sampling to extract the set of all feasible solutions corresponding to various disturbance vectors. Since the one-way sampling-thenoptimization approach does not guarantee the probabilistic feasibility, we employ a hybrid simulationoptimization approach to ensure that the solutions provided by the ϵ-Conservative model are robust to all uncertainty scenarios. The experimental results confirm the scalability of the proposed methodology by generating the robust optimal solutions, satisfying all conservatism levels and uncertainty scenarios irrespective of the problem size.

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Section: Literature Reviewmentioning

confidence: 99%

“…Subject to:(2), (3), (9)-(11),(14);(18),(19)) is the revised version of (1). -CMTSP does not change the computational tractability as it has the same size and complexity as 2.…”

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confidence: 99%

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

2021

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“…These maintenance activities can be divided into two categories. Firstly, the scheduled maintenance, which is to be conducted periodically after a certain flying hours or predicted period of time and secondly, is the unscheduled maintenance which is conducted when the aircraft is declared unserviceable due to any systems or components failure [2], [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Cost Minimization of Aircraft Critical Components for Planning and Maintenance Requirements

Rahim

Noor

Abdullah

et al. 2020

IJIE

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Spare parts management of the aircrafts is a part of maintenance planning that requires effective and efficient planning in order to reduce aircraft downtime in maintenance processes. Spare parts unavailability during maintenance is one of the factors that affects operational availability of the aircrafts fleet. This study focused on identifying the current problem affecting operational availability of the aircrafts fleet, developing an optimization model for cost minimization of spare parts and assessing the impact on spare parts availability using the cost minimization optimization model. Data analysis using machine learning techniques in WEKA was used to identify the current problem that is affecting aircrafts fleet operational availability. Then, Linear Integer Programming (LIP) and Goal Programming (GP) methods were used to develop the cost minimization optimization model by considering the current stock level of the critical components and the budget constrain. From this study, we discovered that spare parts unavailability during maintenance was the biggest contributing factor to the operational availability of the aircrafts fleet. Besides that, the cost minimization optimization model developed in the research had produced optimum level of inventory for the critical components with minimum cost. Spare parts availability for the aircrafts fleet had been improved with the application of the model which directly maximizes the operational availability of the aircraft fleet.

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“…In other work, Kozanidis, Gavranis, and Liberopoulos develop heuristic procedures for solving large instances of the above formulations, and Kozanidis, Gavranis, and Kostarelou consider a non-linear mixed integer formulation. 12,13 Safaei present a mixed integer programming model for scheduling the maintenance activities and the flight missions. 14 In the model, a constraint on the number of available aircraft is included based on the expected number of failures calculated from historical data.…”

Section: Introductionmentioning

confidence: 99%

Maintenance scheduling of a fleet of fighter aircraft through multi-objective simulation-optimization

Mattila

Virtanen

2014

SIMULATION

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The maintenance scheduling problem of a fleet of fighter aircraft is considered through multi-objective simulationoptimization (MOSO). In the problem, a maintenance schedule consisting of target starting times of the maintenance activities of the aircraft is determined. The objectives are to minimize average deviation between the target and actual starting times of the activities and to maximize average aircraft availability. The objectives depend on the maintenance schedule through complex interactions due to a policy in which the need for maintenance is based on the flight hours of the aircraft cumulated during flight missions. In addition, the durations of the flight missions, maintenance activities, and failure repairs are uncertain. Therefore, an MOSO approach is applied to the problem. The approach includes a discrete-event simulation model and a state-of-the art multi-objective simulated annealing algorithm for determining non-dominated schedules. Moreover, a multi-attribute value (MAV) function is used for supporting a maintenance decision-maker (DM) in selecting the preferred non-dominated schedule for implementation. The MAV function captures incomplete information on the values of the objectives as well as on the DM's preference statements regarding the weights of the objectives. The approach is implemented as an MOSO tool whereby the DM can consider the complex interactions and uncertainties of the problem which have not been addressed in the existing literature on maintenance scheduling. The approach and the tool are illustrated with a set of test problems as well as a real-life example problem.

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Heuristics for flight and maintenance planning of mission aircraft

Cited by 14 publications

References 10 publications

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

Robust Maintenance Scheduling of Aircraft Fleet: A Hybrid Simulation-Optimization Approach

Cost Minimization of Aircraft Critical Components for Planning and Maintenance Requirements

Maintenance scheduling of a fleet of fighter aircraft through multi-objective simulation-optimization

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