TY - GEN
T1 - Reducing airport emissions with coordinated pushback processes
T2 - 8th International Conference on Computational Logistics, ICCL 2017
AU - Bubalo, Branko
AU - Schulte, Frederik
AU - Voß, Stefan
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Empirical research has shown that airside ground operations imply a significant percentage of overall airport-related emissions. Among those operations, taxiing is one of the most emission-intensive processes, directly related to the initial pushback process that has a significant impact on the taxiing duration of departing flights. Possible approaches for an effective management of pushbacks at an airport are simulation and optimization models. Airside operations at major airports involve a complex interplay of many operations and parties and therefore need to be planned in a coordinated fashion. Yet, existing approaches have not been applied in a comprehensive planning environment for airside operations. In this work, we develop an algorithm-based relocation approach for pushback vehicles that enables an effective minimization of delays and emissions during the taxiing process. As a result alternative sequences of departing flights are evaluated against each other to find the ones with least total emissions and delay. These algorithms are applied in a simulation environment and evaluated against real-world cases. Preliminary results demonstrate that we are able to solve the underlying pushback routing problem in appropriate computational times for dynamic decision support needed at airports.
AB - Empirical research has shown that airside ground operations imply a significant percentage of overall airport-related emissions. Among those operations, taxiing is one of the most emission-intensive processes, directly related to the initial pushback process that has a significant impact on the taxiing duration of departing flights. Possible approaches for an effective management of pushbacks at an airport are simulation and optimization models. Airside operations at major airports involve a complex interplay of many operations and parties and therefore need to be planned in a coordinated fashion. Yet, existing approaches have not been applied in a comprehensive planning environment for airside operations. In this work, we develop an algorithm-based relocation approach for pushback vehicles that enables an effective minimization of delays and emissions during the taxiing process. As a result alternative sequences of departing flights are evaluated against each other to find the ones with least total emissions and delay. These algorithms are applied in a simulation environment and evaluated against real-world cases. Preliminary results demonstrate that we are able to solve the underlying pushback routing problem in appropriate computational times for dynamic decision support needed at airports.
UR - http://www.scopus.com/inward/record.url?scp=85032865101&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-68496-3_38
DO - 10.1007/978-3-319-68496-3_38
M3 - Conference contribution
AN - SCOPUS:85032865101
SN - 9783319684956
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 572
EP - 586
BT - Computational Logistics - 8th International Conference, ICCL 2017, Proceedings
A2 - VoB, Stefan
A2 - Bektas, Tolga
A2 - Coniglio, Stefano
A2 - Martinez-Sykora, Antonio
PB - Springer
Y2 - 18 October 2017 through 20 October 2017
ER -