• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.61-69
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• 2019

The concept of carsharing involves sharing a small number of reserved cars to be used individually by a larger number of people as required. This study examines the operating parameters of one-way carsharing systems in order to determine the appropriate operating conditions that minimizes the lost sales rate. Five operating parameters are tested in this study: the number of stations, the average number of vehicles per station, the rate of one-way trip, the average number of staffs per station, and the relocation policy. The performance of round-trip carsharing systems is also compared to that of one-way carsharing systems. A simulation model is developed and simulations are performed to determine the appropriate combination of operating parameter and levels. The simulation results show that the average number of vehicles per station is the most critical parameter. Other key findings obtained from this research are as follows. First, applying the appropriate relocation policy to one-way carsharing systems can allow more customers to rent vehicles than the traditional round-trip carsharing systems. Second, the appropriate relocation policy should be selected based on the average number of vehicles per station in order to minimize the lost sales rate. Third, the number of stations does not affect the lost sales rate. This study findings will provide tools to understand impact of the carsharing system parameters on the efficiency of the carsharing operations.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.379-389
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• 2014

The purpose of this study is to optimize the patient(examinee) flow in a health examination center via a simulation model and to improve operational efficiency. Two experimentation scenarios were implemented into the simulation model to determine which proposed scenario provides better improvement in terms of the following performance measures: LOS(Length of Stay), staff utilization, and occupancy level. The simulation results demonstrated that there was no significant difference in response results of two scenarios. Although the original motivation of this study was suggest optimal policy for a patient(examinee) flow, the insight into applying simulation in efficiently managing hospital operations is of more value. Simulation approach is a powerful technique that supports efficient decision-making compared to traditional healthcare management approach based on past experience, feelings, and intuition. Therefore, the proposed experimentation model has wide applicability in healthcare systems.

• Korean System Dynamics Review
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• v.4 no.2
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• pp.131-151
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• 2003

Traffic congestion stems from the widespread desires of people to purse certain goals that inevitably overload existing roads every day. he a transportation policy, congestion toll system has been implemented in Seoul, since 1996. The growing concerns on whether the system would achieve sustained results in the future motivated us to investigate the effectiveness of this policy. Developing and running the congestion toll simulation model, we find that this policy is not an effective policy in the long m. The paper indicates the power of system dynamics approach as a tool for evaluating complex policy like a congestion toll, and suggest that city transportation policy maker should approach the problem with systems thinking and analyze the effectiveness of policy on the basis of understanding the dynamic relationships among subsystems.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.4
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• pp.105-112
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• 2022

Recently, many studies using reinforcement learning-based autoscaling have been performed to make autoscaling policies that are adaptive to changes in the environment and meet specific purposes. However, training the reinforcement learning-based Horizontal Pod Autoscaler(HPA) policy in a real environment requires a lot of money and time. And it is not practical to retrain the reinforcement learning-based HPA policy from scratch every time in a real environment. In this paper, we implement a reinforcement learning-based HPA in Kubernetes, and propose a transfer leanring technique using a queuing model-based simulation to accelerate the training of a reinforcement learning-based HPA policy. Pre-training using simulation enabled training the policy through simulation experience without consuming time and resources in the real environment, and by using the transfer learning technique, the cost was reduced by about 42.6% compared to the case without transfer learning technique.

• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.515-530
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• 2023

Purpose : This research aims to develop a data-driven inspection policy for radio stations utilizing the KS Q ISO 2859-1 sampling method, addressing potential regulatory relaxations and impending management challenges. Methods : Using radio station inspection big data from the past six years, we established a simulation model to evaluate the current policy. A new inspection sampling policy framework was designed based on the KS Q ISO 2859-1 method. The study compares the performance of the current and proposed inspection systems, offering insights for an improved inspection strategy. Results : This study introduced a simulation model for inspection system based on the KS Q ISO 2859-1 sampling method. Through various experimental designs, key performance indicators such as non-detection rate and sample proportion were derived, providing foundational data for the new inspection policy. Conclusion : Using big data from radio station inspections, we evaluated current inspection systems and quantitatively compared a new system across diverse scenarios. Our simulation model effectively verified the feasibility and efficiency of the proposed framework. For practical implementation, essential factors such as lot size, inspection cycle, and AQL standards need precise definition and consideration. Enhancing radio station inspections requires a policy-driven approach that factors in socio-economic impacts and solicits feedback from industry participants. Future study should also explore various perspectives related to legislative, institutional, and operational aspects of inspection organizations.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.10a
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• pp.224-228
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• 1999

When we construct a manufacturing plant, optimal design is very important. This paper is to simulate an engine manufacturing flow line for commercial vehicle. The parameters we consider in simulation include facility downtime, tool change time, buffer size between consecutive stations, and time to repair the facility. We use AutoMod to compare the alternatives. The objective is to minimize the total cost. Simulation results provide significant cost saving by improving the current design and policy.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.68-78
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• 2019

Recently, housing prices have surged, and the government has implemented various regulations, such as finance and taxes. Because of the policy, the nationwide housing price have stabilized, but polarization has occurred. Some argue that regulation can adversely affect the actual demand. Therefore, not only the correlation between market variables but also ripple effect of policy has to be analyzed in policy planning and analysis from a microscopic point of view. In this study, a simulation model was developed by integrating system dynamics for analyzing market structure and agent-based model for modeling decision process of market participants. This research applied the financial regulation and the tax regulation to the model and evaluated the policy effectiveness. This study reveals which feedback dominates according to the policies, which have same purpose. It is because market participants make different decision for each policy. Furthermore, there were other ripple effects not only in the policy target submarket but also in other submarket.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.113-123
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• 2012

In this paper, it is examined how the amount of review time per applicant to a college admission officer system is connected with the performance of the selected students after they enter the college. About five years ago, college admission officers system has been introduced to Korea as a government policy. Thus, for most Korean college, there is not enough number of admission officers, while it takes substantial time to find out whether an applicant has potential ability or not. Thus, it is required to find out some policy alternatives to solve this discrepancy. In this paper, a simulation model is built using System Dynamics theory and simulated to understand the relation between the amount of review time and the performance of the selected students. Finally, some implications and policy suggestions are derived from the simulation results.

• Korean System Dynamics Review
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• v.13 no.4
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• pp.57-80
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• 2012

This research studies effect of FDA regulations in pharmaceutical industry on new drug development. System dynamics is implemented to demonstrate dynamic relationship between FDA regulations and R&D costs, firm's profits, sales. This research is focused on clinical trials of new medical entity process 50~60% portion of total development cost. Simulation results say that firm's profit is more sensitive to increasing the regulation than alleviating the regulation and effect of regulation policy make different result depending on the intensity of regulation and policy direction. Our simulation model provides the instrumental means for the policy makers and strategic decision in pharmaceutical industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.133-141
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• 1990

Human blood is a perishable product : it has a legal lifetime of 21 days from collection, during which it can be used for transfusion to a Patient of the same type, and after which it has to be discarded. Therefore, blood must be supplied safely and effectively because it is one of the medical resources which keep humanlife. In this study, the effects of blood issuing policies on average inventory levels and average age of blood at transfusion are determined by simulation applied the theory of absorbing Markov chains. And as a practical study, the daily demand distribution of blood is estimated by using the data of B General Hospital. The distribution estimated follows poisson distribution and the estimator of parameter estimated from the poisson distribution is 0.762. Simulation is done by using the parameter. The most important problem when control blood is the amount of outdata. So we compared random policy with Modified LIFO and Modified FIFO by using outdata. As a results it is shown that Modified LIFO and Modified FIFO by using outdata. As a results it Is shown that Modified LIFO and Modified FIFO present better issuing policy than Random Policy.