A compact optimization model for the tail assignment problem

Khaled, Oumaima; Minoux, Michel; Mousseau, Vincent; Michel, Stéphane; Ceugniet, Xavier

doi:10.1016/j.ejor.2017.06.045

Cited by 24 publications

(9 citation statements)

References 19 publications

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“…Nowadays, the applications are good indicative and shows the necessity of two or more objective, [33][34][35] other than of single objective. Some of the examples of the bi-objective problem to find the efficient solutions are transportation problem, [36][37][38] supply chain problem, 39,40 assignment problem, 41,42 travelling and salesman problem, [43][44][45] cargo loading and unloading, [46][47][48] defence machineries 49 and healthcare. 50 Therefore, we have addressed the bi-objective SLAQPP, that is, (BSLAQPP) where transmission time and hybrid logarithmic reliability are minimized.…”

Section: Introductionmentioning

confidence: 99%

Network modelling and computation of quickest path for service-level agreements using bi-objective optimization

Sharma

Kumar

Talib

et al. 2019

International Journal of Distributed Sensor Networks

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This article addresses the problem related to the reliability of path after transmitting the given amount of data with the service-level agreement cooperation in the computer communication network. The links have associated with service performance factor parameter during the data transmission, and each node is associated with the requested service performance factor. In this article, first we have considered the single objective to minimize the transmission time of the quickest path problem. An algorithm for quickest path problem has been proposed for results, and furthermore, its time complexity has been shown. The problem has been extended with bi-objective optimization of the quickest path problem, which minimizes the transmission time and hybrid logarithmic reliability. An algorithm is proposed for getting the number of efficient solutions for the quickest path problem using label-correcting algorithm. The algorithms are implemented and tested on different standard benchmark network problems provided with the set of Pareto front of the results.

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Section: Introductionmentioning

confidence: 99%

Network modelling and computation of quickest path for service-level agreements using bi-objective optimization

Sharma

Kumar

Talib

et al. 2019

International Journal of Distributed Sensor Networks

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“…Despite many works treating the problem of including maintenance activities in the planning process, few acknowledge the different types of preventive maintenance (Khaled et al , 2017; Khaled et al ., 2018; Martin et al , 2003) and the possibility of having flexibility in maintenance allocation (Munari and Alvarez, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Aircraft routing problem model for fractional fleets using fault prognostics

Barreto

Abrahão

Vianna

2021

JQME

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PurposeThe objective of this work is to provide a novel aircraft allocation model for fractional business aviation. This model may provide decision-makers with alternative routing solutions that take into consideration preventive maintenance and failure prognostics information. The expected results are more efficient routing solutions when compared to conventional planning models, to help decision-makers improve operations and maintenance planning.Design/methodology/approachThe model is a mixed integer linear problem formulation addressing and considering preventive maintenance and failure prognostics for optimal operations. Numerical experiments were performed using both field and synthetic data to validate the proposed method. All instances are solved using branch, price and cut algorithms from open-source software.FindingsThe results obtained in this study show that the use of failure prognostics information in aircraft routing can provide improvements in overall planning. By choosing slightly longer flight legs, the flight cost will increase, but putting an aircraft with a higher risk of failure on a leg inbound to a maintenance base can reduce maintenance and overall operating cost.Originality/valueThe model and method provide decision-makers with routing solutions that consider new aspects of planning, not used in previous works, such as failure. Most of the literature focuses on solving routing problems for large commercial airlines. Considering that, few solutions are found in literature for fractional business operators, which have their own operational particularities, such as a company managing a fleet of aircraft belonging to multiple shareowners. In such operation, clients may not always fly in the aircraft that they are shareowners, but an aircraft from the fractional fleet of the same category. Here, the company managing the aircraft guarantees that an aircraft will be ready to attend client demands in minimum time. One of the major differences from other models of operation is the dynamic nature of its flight demands, thus requiring flexible and agile planning limiting the available time to find a routing solution.

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“…The formulation, typically, includes capacity constraints (passengers and fleet) and conservation of aircraft, flight, and airport flow (Levin, 1971). Khaled et al (2018). Desaulniers et al (1997) and Barnhart et al (1998), published their pioneering work on formulating the FA and the TA using a string-based formulation and solving it using branch and bound.…”

Section: Literature Reviewmentioning

confidence: 99%

“…All the publications mentioned are limited to daily or weekly schedules and assume cyclical repetitions of the flights and hence maintenance operations. Khaled et al (2018), however, caters to individual maintenance requirements for a 30-day plan. Using an improved TSN formulation for the AMR problem, they effectively schedule A checks, constrained by individual aircraft legal remaining FH.…”

Section: Literature Reviewmentioning

confidence: 99%

An optimisation framework for airline fleet maintenance scheduling with tail assignment considerations

Sanchez

Boyacı

Zografos

2020

Transportation Research Part B: Methodological

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Fierce competition between airlines has led to the need of minimising the operating costs while also ensuring quality of service. Given the large proportion of operating costs dedicated to aircraft maintenance, cooperation between airlines and their respective maintenance provider is paramount. In this research, we propose a framework to develop commercially viable and maintenance feasible flight and maintenance schedules. Such framework involves two multiobjective mixed integer linear programming (MMILP) formulations and an iterative algorithm. The first formulation, the airline fleet maintenance scheduling (AMS) with violations, minimises the number of maintenance regulation violations and the number of not airworthy aircraft; subject to limited workshop resources and current maintenance regulations on individual aircraft flying hours. The second formulation, the AMS with tail assignment (TA) allows aircraft to be assigned to different flights. In this case, subject to similar constraints as the first formulation, six lexicographically ordered objective functions are minimised. Namely, the number of violations, maximum resource level, number of tail re-assignments, number of maintenance interventions, overall resource usage, and number of not airworthy aircraft. The iterative algorithm ensures fast computational times while providing good quality solutions. Additionally, by tracking aircraft and using precise flying hours between maintenance opportunities we ensure that the aircraft are airworthy at all times. Computational tests on real flight schedules over a 30-day planning horizon show that even with multiple airlines (6457 flights, 1032 aircraft, 5 maintenance workshops) our solution approach can construct near optimal maintenance schedules within minutes.

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A compact optimization model for the tail assignment problem

Cited by 24 publications

References 19 publications

Network modelling and computation of quickest path for service-level agreements using bi-objective optimization

Network modelling and computation of quickest path for service-level agreements using bi-objective optimization

Aircraft routing problem model for fractional fleets using fault prognostics

An optimisation framework for airline fleet maintenance scheduling with tail assignment considerations

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