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Discrete event simulation model for external yard choice of import container terminal in a port buffer area
Rusgiyarto F.a, Sjafruddin A.a, Frazila R.B.a, Suprayogia
a Civil Engineering Post Graduate Department, Civil Engineering and Environment Faculty, Bandung Institute of Technology, 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]© 2017 Author(s).Increasing container traffic and land acquisition problem for terminal expansion leads to usage of external yard in a port buffer area. This condition influenced the terminal performance because a road which connects the terminal and the external yard was also used by non-container traffic. Location choice problem considered to solve this condition, but the previous research has not taken account a stochastic condition of container arrival rate and service time yet. Bi-level programming framework was used to find optimum location configuration. In the lower-level, there was a problem to construct the equation, which correlated the terminal operation and the road due to different time cycle equilibrium. Container moves from the quay to a terminal gate in a daily unit of time, meanwhile, it moves from the terminal gate to the external yard through the road in a minute unit of time. If the equation formulated in hourly unit equilibrium, it cannot catch up the container movement characteristics in the terminal. Meanwhile, if the equation formulated in daily unit equilibrium, it cannot catch up the road traffic movement characteristics in the road. This problem can be addressed using simulation model. Discrete Event Simulation Model was used to simulate import container flow processes in the container terminal and external yard. Optimum location configuration in the upper-level was the combinatorial problem, which was solved by Full Enumeration approach. The objective function of the external yard location model was to minimize user transport cost (or time) and to maximize operator benefit. Numerical experiment was run for the scenario assumption of two container handling ways, three external yards, and thirty-day simulation periods. Jakarta International Container Terminal (JICT) container characteristics data was referred for the simulation. Based on five runs which were 5, 10, 15, 20, and 30 repetitions, operation one of three available external yards (external yard – 3) was the optimum result. Apparently, the model confirmed the hypothesis that there was an optimum configuration of the external yard. Nevertheless, the model needs detail elaboration related to the objective function and the optimization constraint. It requires detail validation, in term of service time value, distribution pattern, and arrival rate in each unit server modeled in the next step of the research. The model gave unique and relatively consistent value of each run. It was indicated that the method has a chance to solve the research 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][/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][/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/10.1063/1.4985510[/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]