Particle swarm optimization with a mutation operator for solving the preventive aircraft maintenance routing problem

Sarhani, Malek; Ezzinbi, Omar; Afia, Abdellatif El; Benadada, Youssef

doi:10.1109/gol.2016.7731683

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…For this reason, studies in which heuristic approaches are used in the solution of such large-scale problems are frequently encountered in the literature. Some of those approaches are Genetic Algorithm in Yang and Yang [18]; Particle Swarm Optimization in Mohamed et al [12], Sarhani et al [27], Afia and Sarhani [35]; Variable Neighbourhood Search in Al-Thani et al [24], Cui et al [38]; Ant Colony Optimization in Eltoukhy et al [37] and Simulated Annealing in Afsar et al [31].…”

Section: Discussionmentioning

confidence: 99%

“…That is why it can be classified as either a corrective or predictive measure. Sarhani et al [27] modelled the daily AMRP problem, whose aim is to minimise the planned and unplanned maintenance costs, and developed a new particle swarm optimization algorithm integrated with a population diversity-enhancing mutation operator to use as the solution of the problem. Afia and Sarhani [35], an advanced version of Sarhani et al [27], is another study on unplanned maintenance checks.…”

Section: Maintenance Considerationmentioning

confidence: 99%

See 1 more Smart Citation

Aircraft Maintenance Routing Problem – A Literature Survey

Temucin

Tuzkaya

Vayvay

2021

PROMET

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The airline industry has shown significant growth in the last decade according to some indicators such as annual average growth in global air traffic passenger demand and growth rate in the global air transport fleet. This inevitable progress makes the airline industry challenging and forces airline companies to produce a range of solutions that increase consumer loyalty to the brand. These solutions to reduce the high costs encountered in airline operations, prevent delays in planned departure times, improve service quality, or reduce environmental impacts can be diversified according to the need. Although one can refer to past surveys, it is not sufficient to cover the rich literature of airline scheduling, especially for the last decade. This study aims to fill this gap by reviewing the airline operations related papers published between 2009 and 2019, and focus on the ones especially in the aircraft maintenance routing area which seems a promising branch.

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Section: Discussionmentioning

confidence: 99%

Section: Maintenance Considerationmentioning

confidence: 99%

Aircraft Maintenance Routing Problem – A Literature Survey

Temucin

Tuzkaya

Vayvay

2021

PROMET

View full text Add to dashboard Cite

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“…In their model, they modified the connection network to be able to track the accumulated flying time of each aircraft. Sarhani et al [9] extended the model proposed by Sarac et al [6] for the Aircraft maintenance problem and added the case of aircraft on the ground (AOG) situation which is caused by the unscheduled maintenance events. The one day aircraft routing model along with the side constraints of maintenance is the prime focus of the paper and has been used as basis of our research.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Aircraft Maintenance Routing Using Uninformed and Informed Search Algorithms

Babar¹,

Kamal²,

Usman³

et al. 2018

IJMERR

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Airline sector runs on very high operational costs, strict protocols and complex scheduling process. One of the critical aspect influencing these factors is aircraft maintenance routing. In order to get maintenance at regular intervals as per the FAA regulations, an aircraft is required to be routed towards a feasible maintenance station. Aircraft maintenance routing is one of the major factor that influences the decisions throughout the airline operations. This paper proposes a maintenance feasible route generation technique, based on Breadth first search and Dijkstra's Algorithms. The proposed technique is able to produce the maintenance feasible routes while ensuring that the overall maintenance cost is minimized. 

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