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Application of simulated annealing method on aircrew assignment problems in Garuda Indonesia
Sumarti N.a, Rakhman R.N.a, Hadianti R.a, Uttunggadewa S.a
a Department of Mathematics, Institut Teknologi Bandung, 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]© 2012 Newswood Limited. All rights reserved.Problems of flight scheduling consist of the flight rotation pairings and the crew assignment problems. In this paper, we are dealing with the aircrew-assignment problem and its computational aspects that are implemented on data of Garuda Indonesia, a national airline company in Indonesia, serving of at least 42 domestic and international destinations. In this problem, the crew pairing or formally named Crew Rotation Pattern (CROPA) is given as an input to the method of the assignment of aircrews to each of the flights that the company has to cover. There are two issues which will be answered: the minimum number of the aircrew needed for operating the flights for all CROPAs and the allocation of crews to CROPAs with balancing of the flying and duty hours for each crew. The latter problem will be solved by the application of the simulated annealing method, which is a random search method for solving optimization problems. This metod use an analog simulation of the annealing of solids, where the objective function to be minimized corresponds to temperature of the solid. This method allows the occasional acceptance of a new inferior solution in order to avoid being trapped in a local optimum. The lower the temperature, the smaller the chance of this new solution to be accepted. It is shown that the results are satisfactory in finding the solution of the aircrew assignment problem.[/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]Assignment problems,Computational aspects,Computational mathematics,Objective functions,Optimization method,Optimization problems,Random search method,Simulated annealing method[/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]Aircrew-assignment problem,Computational mathematics,Optimization methods,Simulated annealing method[/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]Manuscript received March 31, 2012; revised April 17, 2012. Initial works of this research was supported by Garuda Indonesia research grant, and also in part by IMHERE B.2C FMIPA ITB International Conference Grant.[/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][/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]