Irregular airline operations: a review of the state-of-the-practice in airline operations control centers

Clarke, Matthew

doi:10.1016/s0969-6997(98)00012-x

Cited by 56 publications

(28 citation statements)

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“…Problems originating because of a local event (e.g. aircraft mechanical failure) can trigger other problems and easily propagate to other flights [22,40,41]. Examples of such problems are: -General ATC restriction related.…”

Section: B Disruption Management By An Aoc Centermentioning

confidence: 99%

Agent-Based Modeling and Simulation of Coordination by Airline Operations Control

Bouarfa

Blom

Curran

2016

IEEE Trans. Emerg. Topics Comput.

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Abstract-Motivated by the need to understand and further optimize coordination processes in the socio-technical air transportation system, this paper implements and compares four coordination policies through agent based modelling and simulation (ABMS). Three policies are based on established practices, while a fourth is based on the joint activity coordination theory from the psychology research domain. For each of these four policies, the relation with the literature on coordination is identified. The specific application of the four policies concerns Airline Operations Control (AOC), which core's functionality is one of coordination and taking corrective actions in response to a large variety of airline operational disruptions. In order to evaluate the four policies, an agent based model of the AOC and crew processes has been developed. Subsequently, this agent based model is used to assess the effects of the four AOC policies on a challenging airline disruption scenario. For the specific scenario considered, the joint-activity coordination based AOC policy outperforms the other three policies. More importantly, the simulation results provide novel insight in operational effects of each of the four AOC policies, which demonstrates that ABMS allows to analyze the effectiveness of different coordination policies in the highly complex socio-technical air transportation system.

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Section: B Disruption Management By An Aoc Centermentioning

confidence: 99%

Agent-Based Modeling and Simulation of Coordination by Airline Operations Control

Bouarfa

Blom

Curran

2016

IEEE Trans. Emerg. Topics Comput.

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“…Since the quality of their decisions are not displayed, they could not, in some cases until aftermath, find out that actions, such as to delay or cancel flights, were unnecessary decisions [25]. The proposed tool takes into consideration the above shown factors as most influencing on the decision making process for a particular flight which may tend to expand to one disruptive flight if not handled timely, potentially impacting also the downstream flights.…”

Section: Operational Situation and Research Objectivementioning

confidence: 99%

A decision support tool for evaluating decision options for out-bound flight delays considering high-valuable passengers

Radivojevic

Milbredt

2015

Eur. Transp. Res. Rev.

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Introduction Though studies show that arriving on-time is the service characteristic most valued by the air passengers and passenger service coordinators are consulted in the operation disruptions, passengers rarely drive operational decisionmaking in the disruption management of an airline. Taking into consideration airlines' seeking the prevention of losing passengers' goodwill in situations where the level of service quality (SQ) performed is not as high as the promoted one, this research is focused particularly on an influence of delayed connecting (or in-bound) high-fare passengers on making decisions on onward delays. Operationally seen, connecting passengers are of a particular importance for airlines, since they are already involved in their operations-flow, while becoming in this way the third most important airlines' aspect of operations, succeeding aircraft and crew. On the other hand, exclusive travellers such as first class and elite-status, contracted corporate members, and business passengers are considered as the high-valuable passengers, who are enough (financially) worth to the airline, particularly for to be waited for if they are delayed in arriving with an in-bound flight. Based upon an examination made from the airlines' operational point of view and for determined prioritization strategy, a Decision Support System (DSS) tool, named DEVOTED DSS Tool, for use in the disruption management of the Airline Operation Control Centre (AOCC) is presented. For assisting the airline operation controllers in decisions on whether to delay the departure of out-bound flights in order to wait for arriving-delayed highfare passengers from an in-bound flight, an influence of these passengers' satisfaction on making decisions on onward delays, the passenger segmentation per flight, associated consequences in terms of the Level of Service (LOS) performed by the carrier and the one perceived by the passengers, as well as the accompanying costs are taken into account. Methods The designed tool incorporates the key elements of Human-Centred Design (HCD) relying on a multi-criteria algorithm making-up its decision making process for evaluation of decision options and making suggestion. Being scenariodriven and knowledge-based the tool implements the airline prioritisation policies. Hereby, the level of service quality delivered by the air carrier and the level of service quality expected and perceived by the high-fare passengers are determined quantitatively by employing a created LOS-model which relies on the basic categorization rules of the Kano's quality model. Results For testing of the tool, two scheduled airlines with two different prioritization strategies and operating on the same flight route between the same origin-destination airports (i.e. city-pairs) are taken. Though the testing is real-world data based, in order to expose a tangible aim and capabilities of the designed tool, the testing scenarios are constructed in such a way to reflect specific borderline operational situations, while emph...

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“…In "Irregular Airline Operations: A Review of the State-of-the-practice in Airline Operations Control Centers" from 1998 [15] Clarke provides an overview of the state-of-thepractice in Operations Control Centers (OCC) in the airline industry in the aftermath of irregular operations. The overview is based on field studies to several airlines.…”

Section: Disruption Managementmentioning

confidence: 99%

Disruption management in the airline industry—Concepts, models and methods

Clausen

Larsen

et al. 2010

Computers & Operations Research

268

118

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The airline industry is notably one of the success stories with respect to the use of optimization based methods and tools in planning. Both in planning of the assignment of available aircraft to flights and in crew scheduling, these methods play a major role.Plans are usually made several months prior to the actual day of operation. As a consequence, changes often occur in the period from the construction of the plan to the day of operation. Optimization tools play an important role also in handling these changes.However, at the day of operation, no planning tool have been able to cope with the complexity of the re-planning given that the time span for proposing a solution is only a few minutes. Numerous suggestions for such subsystems have been put forward, but today no general tool is able to handle aircraft, crew, and passenger concurrently in a single system. Currently, there is a gap between the reality faced in operations control and the decision support offered by the commercial it-systems targeting the recovery process. Though substantial achievements have been made with respect to solution methods, and hardware has become much more powerful, even the most advanced prototype systems for integrated recovery have severe limitations.The current review accounts for the majority of subsystems mentioned in the literature in terms of the sub-problem addressed and the method used in each particular contribution. For each proposed system, also the computational experiments supporting the practical usability of the system is reported.

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Irregular airline operations: a review of the state-of-the-practice in airline operations control centers

Cited by 56 publications

References 0 publications

Agent-Based Modeling and Simulation of Coordination by Airline Operations Control

Agent-Based Modeling and Simulation of Coordination by Airline Operations Control

A decision support tool for evaluating decision options for out-bound flight delays considering high-valuable passengers

Disruption management in the airline industry—Concepts, models and methods

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