A branch-and-price approach for operational aircraft maintenance routing

Sarac, A. Sezai̇; Batta, Rajan; Rump, Christopher M.

doi:10.1016/j.ejor.2004.10.033

Cited by 114 publications

(75 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The studies relation to the airline problems can be classified into three groups: fleeting-related problems, routing-related problems, and aircraft recovery problems (Sarac et al 2006). The aircraft schedule recovery problem fell into the last category and it is a typical NP-hard optimization problem.…”

Section: Aircraft Schedule Recovery Problemmentioning

confidence: 99%

Cat Swarm Optimization Algorithm

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

View full text Add to dashboard Cite

In this chapter, we present a new population-based method, called cat swarm optimization (CSO) algorithm, which imitates the natural behaviour of cats. We first describe the general knowledge of the behaviour of cats in Sect. 6.1. Then, the fundamentals and performance of CSO are introduced in Sect. 6.2. Next, some selected variations of CSO are explained in Sect. 6.3. Right after this, Sect. 6.4 presents a representative CSO application. Finally, Sect. 6.5 summarises this chapter. IntroductionCats exhibit fascinated social behaviours that have long since attracted the attention of human beings. When we were young, we may have observed that cats have a strong curiosity towards moving objects. We may have also discovered that even though cats spend most of their time in resting, they always remain alert and can possess a good hunting skill. Inspired by these behavioural pattern, Chu and Tsai (2007) proposed a new optimization algorithm called cat swarm optimization (CSO) that involves two modes (i.e., seeking and tracing) of operations for solving complex optimization problems. Behaviour of CatsNowadays, one of the most popular companion animals can be found in homes throughout the world is the domestic cats. However, cat social behaviour is complex and incompletely understood. Recently, researchers have focused their attention on two categories, i.e., resting behaviour and chasing behaviour.

show abstract

Section: Aircraft Schedule Recovery Problemmentioning

confidence: 99%

Cat Swarm Optimization Algorithm

Xing

Gao²

2013

Innovative Computational Intelligence: A Rough Guide to 134 Clever Algorithms

View full text Add to dashboard Cite

show abstract

“…Therefore, a weekly schedule is derived by solving a sequence of daily problems. The main advantages of addressing a daily operational problem are the ability to both accurately take into account the legal remaining flying time, and also to recover from unplanned disruptions [44]. The AMRP for fleet type f (f = 1, .…”

Section: Extension To Maintenance-dependent Routingmentioning

confidence: 99%

Exact approaches for integrated aircraft fleeting and routing at TunisAir

et al. 2009

View full text Add to dashboard Cite

We describe models and exact solutions approaches for an integrated aircraft fleeting and routing problem arising at TunisAir. Given a schedule of flights to be flown, the problem consists of determining a minimum cost route assignment for each aircraft so as to cover each flight by exactly one aircraft while satisfying maintenance activity constraints. We investigate two tailored approaches for this problem: Benders decomposition and branch-and-price. Computational experiments conducted on real-data provide evidence that the branch-and-price approach outperforms the Benders decomposition approach and delivers optimal solutions within moderate CPU times. On the other hand, the Benders algorithm yields very quickly high quality near-optimal solutions.

show abstract

“…Each of the above models has its advantages and disadvantages. It has been demonstrated that a branch-and-price approach can be used to solve operational aircraft maintenance routing problem that the airlines face on a daily basis [37]. Lu et al propose a virtual maintenance environment, in which maintenance task virtual simulation can be conducted to support maintainability concurrent design of aircraft system [27].…”

Section: Aircraft Maintenancementioning

confidence: 99%

Aircraft fault forecasting at maintenance service on the basis of historic data and aircraft parameters

Pogačnik¹,

Duhovnik²,

Tavčar³

2017

EiN

View full text Add to dashboard Cite

AircrAft fAult forecAsting At mAintenAnce service on the bAsis of historic dAtA And AircrAft pArAmeters prognozowAnie uszkodzeń stAtków powietrznych dlA celów obsługi konserwAcyjnej nA podstAwie ich pArAmetrów orAz dAnych z eksploAtAcji PogAčnik B, Duhovnik J, TAvčAr J. Aircraft fault forecasting at maintenance service on the basis of historic data and aircraft parameters. Eksploatacja i niezawodnosc -Maintenance and reliability 2017; 19 (4): 624-633, http://dx

show abstract

A branch-and-price approach for operational aircraft maintenance routing

Cited by 114 publications

References 27 publications

Cat Swarm Optimization Algorithm

Cat Swarm Optimization Algorithm

Exact approaches for integrated aircraft fleeting and routing at TunisAir

Aircraft fault forecasting at maintenance service on the basis of historic data and aircraft parameters

Contact Info

Product

Resources

About