• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.239-246
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• 2009

In this study, we analyze the mean waiting time on the nested open queueing network, where the population within each subnetwork is controlled by a semaphore queue. The queueing network can be transformed into a simpler queueing network in terms of customers waiting time. A major characteristic of this model is that the lower layer flow is halted by the state of higher layer. Since this type of queueing network does not have exact solutions for performance measure, the lower bound and upper bound on the mean waiting time are checked by comparing them with the mean waiting time in the transformed nested queueing network. Simulation estimates are obtained assuming Poisson arrivals and other phase-type arrival process, i.e., Erlang and hyper-exponential distributions. The bounds obtained can be applied to get more close approximation using the suitable approach.

• Journal of Fisheries and Marine Sciences Education
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• v.10 no.1
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• pp.1-14
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• 1998

Transportation provides an infrastructure vital to economic growth, and it is also an integral part of production. As a port is regarded as the interface between the maritime transport and domestic transport sectors, it certainly play a key role in any economic development. Ship's delay caused by port congestion has recently has recently attracted attended with the analysis of overall operation in port. In order to analyse complicated port operation which contains large number of variable factors, queueing theory is needed to be adopted, which is applicable to a large scale transportation system in chiding ship's delay in Inchon port in relation to ship's delay problem. The overall findings are as follows ; 1. The stucture of queueing model in this port can be represented as a complex of multi-channel single-phase 2. Ship's arrival and service pattern were Poisson Input Erlangian Service. 3. The suitable formula to calculate the mean delay in this port, namely, $W_q={\frac{{\rho}}{{\lambda}(1-{\rho})}}{\frac{e{\small{N}}({\rho}{\cdot}N)}{D_{N-1}({\rho}{\cdot}N)}}$ Where, ${\lambda}$ : mean arrival rate ${\mu}$ : mean servicing rate N : number of servicing channel ${\rho}$ : utilization rate (l/Nm) $e{\small{N}}$ : the Poisson function $D_{(n-1)}$ : a function of the cumulative Poisson function 4. The utility rate is 95.0 percents in general piers, 75.39 percents in container piers, and watiting time 28.43 hours in general piers, 13.67 hours in container piers, and the length of queue is 6.17 ships in general piers, 0.93 ships in container piers, and the ship turnaround time is 107.03 hours in general piers, 51.93 hours in container piers.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.33-46
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• 2022

This paper, in order to minimize the ground waiting time of an Air tanker, the queuing theory, that is, a queue that calculates the waiting time under single-server and multi-server situations, was used in the study. Since the national budget and resources are limited, the unlimited increase of the logistics support service team is limited. Therefore, the number of logistic support service teams that can adaptively control the ground waiting time according to the wartime preparation stage or war environment was calculated. The results of this study provide a stipulated standard for calculating the optimal number of air tanker logistic support service teams of the Air Force, providing a basis for the logistical commander to assign logistic support service teams to each stage from peacetime to wartime.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.5 no.1 s.9
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• pp.1-12
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• 2006

In order to estimate a dynamic origin and destination demand between on and off-ramps in the freeways, a traffic flow theory can be used to calculate a link distribution proportion of traffics moving between them. We have developed a dynamic traffic estimation model based on the three-phase traffic theory (Kerner, 2004), which explains the complexity of traffic phenomena based on phase transitions among free-flow, synchronized flow and moving jam phases, and on their complex nonlinear spatiotemporal features. The developed model explains and estimates traffic congestion in terms of speed breakdown, phase transition and queue propagation. We have estimated the link, on and off-ramp volumes at every time interval by using traffic data collected from vehicle detection systems in Korea freeway sections. The analyzed results show that the developed model describes traffic flows adequately.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.115-131
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• 2001

The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.