• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.119-129
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• 2019

Although line production systems with finite buffers have been studied over several decades, except for some special cases there are no explicit expressions for system performances such as waiting times(or response time) and blocking probability. Recently, a max-plus algebraic approach for buffer-sharing systems with constant processing times was introduced and it can lead to analytic expressions for (higher) moment and tail probability of stationary waiting. Theoretically this approach can be applied to general processing times, but it cannot give a proper way for computing performance measures. To this end, in this study we developed simulation models using @RISK software and the expressions derived from max-plus algebra, and computed and compared blocking probability, waiting time (or response time) with respect to two blocking policies: communication(BBS: Blocking Before Service) and production(BAS: Blocking After Service). Moreover, an optimization problem which determines the minimum shared-buffer capacity satisfying a predetermined QoS(quality of service) is also considered.

• 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.

• 대한예방의학회:학술대회논문집
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• 1995.10a
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• pp.237-238
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• 1995

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.374-378
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• 2001

We present a discrete-time version of the distributional Little's law, of which the continuous-time version is well known. Then we extend it to the queue in which two or more customers may depart at the same time. As a demonstration, we apply this law to various discrete-time queues such as the standard Geom/G/1 queue, the Geom/G/1 queue with vacations, the multi-server Geom/D/c queue, and the bulk-service Geom/$G^b$/1 queue. As a result, we obtain the probability generating functions of the numbers in system/queue and the waiting times in system/queue for those queues.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.66-71
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• 2003

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.

• Proceedings of the KSR Conference
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• 1998.05a
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• pp.160-171
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• 1998

Express subway system is one of the effective systems adapting to improve service level. Express trains make fewer passenger stop, using a double track or a bypass track, than local trains which served all stations, Express service has been very popular with passengers who travel uninterrupted between terminals, but is has generated some dissatisfaction among passengers who experience longer waiting time on stations. This study aims at proposing the methodology to analyze changes of travel pattern in subway system adapting the express service and to estimate the time saving effects resulting from the installation of the express system. This methodology is evaluated in the fifth line under an assumpt ion that express subway system are adapted. Based on the results of the case study, the following conclusions are made: First, express system reduce a total travel time of 13% or above. Second, shorter headway of express trains increases the time saving effects on subway system. although it requests more waiting time to local train passenger. Third, an installation of Express system to Seoul subway system can augment subway demand in seoul metropolitan area.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.175-181
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• 2002

BIS(Bus arrival Information System) is a system that informs Passengers waiting at bus stops of the bus arrival time of next buses. However, when operating this system, it is not exactly known what type of bus arrival information should be provided. The purpose of this paper is to develop a model of the optimal bus arrival time to be informed for BIS. Analyzing Efficiency in the Seoul's Urban Bus Industry Using Data Envelopment Analysis. Two basic types of bus arrival information can be considered. One is Bus Locations : Where next buses are located and under what situation they are, such as the next bus departed from the previous stop, The other is Expected Arrival Time. Time to the arrivals of next buses. Characteristics of these two types of bus arrival time information provided for passengers waiting at bus stops for BIS are examined. The waiting time of passengers at bus stops is derived as a function of the bus arrival time to be informed. Some basic principles about the optimal bus arrival time to be informed are found. Finally, a case study assuming several simplifications is performed. One of the key findings is that there exists optimal arrival time to be informed other than the average arrival time. The optimal arrival time to be informed should be closer to the average arrival time for small and very large standard deviations and be earlier for certain amounts of standard deviations.

• Journal of Families and Better Life
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• v.19 no.1
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• pp.95-110
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• 2001

Recently a number of large discount store and those of its users was increasing. The purpose of this study is to investigate the tendency of impulse buying and analyzes factors which influence impulse buying. The data had been collected from questionaries with 474 consumers who visit large discount store. The major statistical methods used for data analysis are frequency, percentile, mean, t-test, multiple regression analysis, one-way ANOVA, and Duncans multiple range test utilizing SPSS Win pc+program. The results of this study are as follows : 1. The four different kind of impulse buying is measured. The overall level of impulse buying is 2.76. Suggestion impulse buying(M=3.19) is the highest, and the lowest is pure impulse buying(M=2.66). 2. In the area of demographic variables is significantly different in the age of twenties and thirties(p<.05). A visit frequency and membership. In the area of in-store variables is significantly different by all factors at impulse buying except waiting time. Especially, point-of-purchase(POP) advertisement and discount sale are very important variables. A visit frequency and membership are significantly different in the area of consumer-related variables. 3. Waiting time, a visit frequency, a POP advertisement, and a discount sale have the positive effects on overall impulse buying. Pure impulse buying is influenced by shopping list, POP advertisement and a stores atmospher. Buying companion, membership, kind of store and waiting time have the effect on reminder impulse buying. Suggestion impulse buying is influenced by school career, shopping list and POP advertisement. Planned impulse buying is influenced by sex, POP advertisement, buying companion and discount sale.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.5
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• pp.453-461
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• 1989

Mean waiting time for each priority packet of each node in packet based priority token ring local area networks(LAN) was approximately analyzed using Bux's token ring LAN results which have not considered priority and Cohbam's head of line(HOL) priority results. In this paper, priority reservation method suggested in the IEEE 802.5 standard was not used. Relative error between numerical results which was presented in this paper and simulation results was identified by +-5%. For traffic intenity, number of node, packet length, transmission speed, line length, token latency, number of priority class and traffic percentage to some heavy trafficd node, mean waiting time of each priority was analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8B
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• pp.780-786
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• 2002

In this paper several access schemes for voice and data packet over CPCH with waiting time signalling are proposed. Waiting time signalling is used for reducing the excessive attempt of UE when all the CPCH channel resources is being used by other UEs. The proposed schemes in this paper are better than other schemes in view of the voice/data packets? dropping probability, average access attempt to transmit voice/data packets successfully and the average throughput.