• Industrial Engineering and Management Systems
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• 제7권2호
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• pp.133-142
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• 2008

The Emergency Department (ED) is an integral part of hospitals. Admissions from the ED account for a significant proportion for a hospital's activity. Ensuring a timely and efficient flow of patients through the ED is crucial for optimising patient care. In recent years, ED overcrowding and its impact on patient flow has become a major issue facing the health sector. Simulation is rapidly becoming a tool of choice when examining hospital systems due to its capacity to involve numerous factors and interactions that impact the system. An analytical simulation model is used to investigate potential impacts by changing the following aspects of ED (physical layouts; number of beds; number and rate of patient arrivals; acuity of illness or injury of patients; access to radiology and pathology services; hospital staffing arrangements; and access to inpatient beds). Results of a significant numerical investigation at a hospital are also presented.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.169-173
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• 2015

The linear scheduling method or line-of-balance (LOB) is a popular choice for projects that involve repetitive tasks during project execution. The method, however, produces deterministic schedule that does not convey a range of potential project outcomes under uncertainty. This results from the fact the basic scheduling parameters such as crew production rates are estimated to be deterministic based on single-point value inputs. The current linear scheduling technique, therefore, lacks the capability of reflecting the fluctuating nature of the project operation. In this paper the authors address the issue of how the variability of operation and production rates affects schedule outcomes and show a more realistic description of what might be a realistic picture of typical projects. The authors provide a solution by providing a more effective and comprehensive way of incorporating the crew performance variability using a Monte Carlo simulation technique. The simulation outcomes are discussed in terms of how this stochastic approach can overcome the shortcomings of the conventional linear scheduling technique and provide optimum schedule solutions.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2000년도 전력전자학술대회 논문집
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• pp.460-463
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• 2000

Fuzzy logic control(FLC) has been studied extensively and has been applied in various applications. The most popular control strategy takes the Fuzzy Proportional-Integral(FPI) form while systematic methods have been developed to derive the fuzzy rules and membership functions the choice of the scaling factors remains an open problem, In this paper an analytical FPI scaling factor determining method is derived based on the functional equivalence of the PI and FPI controllers. Simulation have been carried out with a brushless DC motor drive system as test-bed the obtained results drive system as test-bed the obtained results have verified that the derived method is applicable to both the initial choice and further tuning of the FPI scaling factors.

• 전기학회논문지
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• 제58권8호
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• pp.1633-1637
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• 2009

We propose a new technique for sidelobe suppression in orthogonal frequency division multiplexing (OFDM) systems. Sidelobe suppression is an essential technique to design OFDM based overlay system. The proposed technique is based on the combination of the multiple choice sequence (MCS) with the conventional windowing of OFDM signal in time domain. The MCS is choosing the one sequence which has lowest power in sidelobes from the produced set of sequences. The main advantage of proposed technique is that it fully utilizes the available bandwidth to transmit data. Simulation results show that by combining MCS with conventional windowing technique, the sidelobes in OFDM system can be significantly reduced

• 경영과학
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• 제29권2호
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• pp.91-103
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• 2012

Revenue management problems originated in the 1970's in the context of the airline industry have been successfully introduced in airline industries. It has started on the capacity control by booking classes for available seats, and has been recognized as a powerful tool to maximize the total revenue. Changing customer behavior and airline market environments, however, has required a new mechanism for improving the revenue. Dynamic pricing is one of innovative tools which is to adjust prices according to the market status. In this paper, we consider a dynamic pricing and seat control problem for discrete time horizon. The problem can be modeled as a stochastic programming problem. Applying the linear approximation technique and given the price set for each time, we suggest a mixed Integer Programming model to solve our problem efficiently. From the simulation results, we can find our model makes good performance and can be expanded to other comprehensive problems.

• 분석과학
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• 제8권4호
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• pp.707-714
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• 1995

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonstrates its excellent utility for the complex depth profile system. It includes the stable restoration of the depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 춘계 학술대회 논문집
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• pp.31-35
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• 2001

Simulation --- The ideal tool for BPR. Work now and CASE tools are static modeling tools. Based on our own customers surveys, we have discovered that the use of process modeling tools thus far has focused on modeling the current(What-Is) state of a business. We have found that 90 percent of reengineering projects, the modeling tools of choice have been flowcharting tools. Static models offer help in understanding the overall nature of an existing process. However, static models can not really help you see the step by step motions towards completion of your goals. In static modeling, you see two pictures in time, usually taken at the current state and final state models of your reengineering project. Static models are usually not object oriented, therefore can not show facility or office layout and movement of entities and objects throughout the facility. However, this does not mean that static modeling does not have its application nor add value to the user as in a few success stories. Simulation helps the team analyze the complex aspects of the project. Many times a plan that looks good on paper might turn out entirely different when put into action. Therefore, simulation helps you look at how situations might work before actual implementation. In particular, computer simulation models help you view a reengineered condition before they are rolled-out. Items such as a lead time and resource allocation.

• 자원ㆍ환경경제연구
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• 제21권2호
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• pp.237-269
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• 2012

본 연구는 수송부문 $CO_2$ 배출량 저감을 목표로 하는 친환경자동차에 대한 지원정책의 효과를 예측하고 정책성공의 결정요인을 분석하는 것을 목적으로 한다. 자동차 이용에서 발생하는 $CO_2$ 배출량은 자동차의 유형을 선택하는 이산선택행위와 이미 선택한 유형의 자동차를 어느 정도나 운행하는지를 결정하는 연속선택행위에 의해서 영향을 받는다. 본 연구는 이산 및 연속 선택을 결합분석하는 이산 연속선택모형을 구축한 후, 한국 소비자들의 자동차 선택 및 운행거리 자료에 적용하여 자동차의 연료효율에 따라 보조금 부과금을 차등 적용하는 정책을 시행할 때 발생하는 두 가지 선택의 변화를 동시에 분석하였다. 분석 결과에 의하면 보조금 부과금이 도입되는 방식이나 상대적 크기에 따라 전기자동차나 하이브리드 자동차와 같은 새로운 유형의 친환경자동차의 예상보급률이 달라지며, $CO_2$ 배출량 저감 수준에 있어서도 상당한 차이를 나타내었다. 또한 보조금 부과금을 적절히 선택할 경우에만 정부의 세입중립성을 유지하면서도 정책효과를 거둘 수 있을 것이라는 분석 결과도 도출되었다. 따라서 연비에 따라 차등 적용되는 보조금 부과금 형태 정책의 성공 여부는 정책이 새로운 유형의 친환경자동차의 점유율에 실질적인 차이를 유발하도록 설계되었는지에 달려있다고 할 수 있다.

• 자원ㆍ환경경제연구
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• 제16권3호
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• pp.683-699
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• 2007

이 연구는 선택실험법(CE)을 이용하여 다속성 사망 위험 감소와 관련된 선택들로부터 확률적 인간생명 가치(VSL)를 추정하였다. 사망 위험의 네 가지 속성들(사망 원인, 사망위험의 자발성, 사망 시기, 사망 위험 감소의 크기)을 이용하여 선택 대안들의 집합을 설계하였다. 다항 로짓모형의 추정 결과는 10년 동안 1/1,000의 사망 위험을 감소하기 위해 연간 27,930원, 성인의 사망 위험 감소를 위해 연간 116,773원, 자발적 사망 위험 감소를 위해 연간 97,682원, 비자발적 사망 위험 감소를 위해 연간 77,234원을 지불하려고 하였다. 이로부터 얻어진 다양한 확률적 인간생명가치로는 청소년 이하(18세 미만)인 경우 11.65~13.67억 원, 성인(18~59세)은 16.31~18.33억 원, 노인(60세 이상)의 경우는 11.28~13.30억 원으로 추정되었다.

• 대한산업공학회지
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• 제23권4호
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.