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Scheduling model for air traffic in Indonesia
Caroline M.L.a, Asnar Y.a, Kistijantoro A.I.a
a Informatics Study Program, SEEI – Bandung Institute of Technology, Malaysia
[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]© 2016 IEEE.Congestion because of increasing demand of air transportation occurs at several airports in Indonesia especially Soekarno-Hatta International Airport. In 2013, Soekarno-Hatta International Airport ranked 25th busiest airports in the world by Airports Council International. One of several ways to enlarge capacity of airports is to improve efficiency current infrastructure utilization with optimizing schedule. Three referred optimization models are model of Beasley et al. which optimizes runway utilization, Bertsimas and Stock Patterson’s model which optimizes air space capacity allocation and Lulli and Odoni’s model which are macroscopic model of Bertsimas and Stock Patterson’s model. Unfortunately, Lulli and Odoni’s model cannot studied further because of lack information about increasing convex function. The other models modified from integer program to constraint satisfaction optimization program (CSOP) so that the models are flexible to modify and the solution can be local optimum. Because of these advantages, rescheduling can be performed when there was little change in flight schedule. In addition, several constraints are added to modification of model of Beasley et al. such as flight continued constraint. Based on tests, modification of model of Beasley et al. success to reduce delays and modification of Bertsimas and Stock Patterson’s model success to do a 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=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Air space,Integer program,Optimization modeling,Optimization programs,Optimization scheduling[/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]air space allocation optimization model,constraint satisfaction optimization program (CSOP),integer program,Optimization scheduling model,runway optimization model[/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/10.1109/TENCONSpring.2016.7519382[/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]