2017
DOI: 10.1007/978-3-319-60285-1_1
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Agent Based Model for Hub Operations Cost Reduction

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Cited by 2 publications
(3 citation statements)
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“…Different approaches propose an integrated recovery that considers both aircraft re-routing and passengers (Jozefowiez et al, 2013;Hu et al, 2016). Delgado et al (2016) combine two strategies for airlines to recover from delays in a hub strategy. The first strategy relies on dynamic cost indexing, which allows aircraft to be accelerated to recover delays, while the other relies on delaying departing aircraft to wait for connecting passengers.…”
Section: Tactical Handling Of Airside Operationsmentioning
confidence: 99%
See 1 more Smart Citation
“…Different approaches propose an integrated recovery that considers both aircraft re-routing and passengers (Jozefowiez et al, 2013;Hu et al, 2016). Delgado et al (2016) combine two strategies for airlines to recover from delays in a hub strategy. The first strategy relies on dynamic cost indexing, which allows aircraft to be accelerated to recover delays, while the other relies on delaying departing aircraft to wait for connecting passengers.…”
Section: Tactical Handling Of Airside Operationsmentioning
confidence: 99%
“…Delgado et al. (2016) combine two strategies for airlines to recover from delays in a hub strategy. The first strategy relies on dynamic cost indexing, which allows aircraft to be accelerated to recover delays, while the other relies on delaying departing aircraft to wait for connecting passengers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Agent-based models (ABM) used as the basis for a network approach of system design are relatively new in the ATM domain. ABMs that can be found in this field in the literature (Bouarfa et al, 2013;Stroeve et al, 2013;Molina et al, 2014;Gurtner et al, 2017;Delgado et al, 2017) are usually used to assess the impact of fairly limited changes in the airspace and/or are focused on a relatively small geographical area. For instance, some research projects modelled passenger flows in airport terminals as multi-agent systems (Enciso et al, 2016;Schultz and Fricke, 2011).…”
Section: Agent-based Models and Air Traffic Managementmentioning
confidence: 99%