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Simulation for measuring the effect of flight retiming to the robustness of flight schedule
Novianingsih K.a,b, Hadianti R.a, Uttunggadewa S.a, Soewono E.a
a Department of Mathematics, Institut Teknologi Bandung, Indonesia
b Department of Mathematics Education, Faculty of Mathematics and Natural Science Education, Universitas Pendidikan Indonesia, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]In day-to-day operations, flight delays might happen due to some reason such as bad weather conditions, equipment failure, and limited runway capacity. Flight delays do not only increase crew operating cost, they can cause delay propagation on subsequent flights. Since the crew cost is the second largest cost, it is important to construct a robust flight schedule where any flight delay will not lead to a massive disruption to the subsequent downstream flights. In this paper, we analyze the effect of flight retiming to the robustness of flight schedule. We construct a simulation for measuring the robustness of the flight schedule, where the probability of crew pairing found after a number of flight delays happen is used as the measure of robustness. It is shown that the retiming will increase the robustness of the schedule if we only retime the flights which appear in the first cycle of the set of selected pairings. © 2014 AIP Publishing LLC.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Crew pairing,Day-to-day operations,Delay propagation,Equipment failures,Flight schedules,Retiming,Runway capacity,simulation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]crew pairing,Flight retiming,optimization,robust flight schedule,simulation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1063/1.4868840[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]