• 품질경영학회지
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• 제24권3호
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• pp.31-36
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• 1996

A Markovian stochastic model for a system subject to random shocks is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arrives at the system periodically for inspection and repairs the system only if the state is below a threshold. Costs are assigned to each inspection of the repairman, to each repair, and to the system being in bad states below the threshold. The expected long run average cost is obtained and compared with that of the random inspection introduced by Lee and Lee(1994).

• 산업경영시스템학회지
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• 제44권4호
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• 대한교통학회지
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• 제27권6호
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• pp.147-156
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• 2009

본 논문에서는 기 운영되고 있는 도시부 대중교통을 대상으로 노선의 운행빈도 설계 문제의 모델링 및 해법 개발을 위한 방법론을 제시하였다. 개발된 운행빈도 모형은 이중구조 모형으로서 상위 운영자 모형은 이용 가능한 총 차량 대수제약과 최소/최대 운행빈도 제약 하에 비용과 수익을 모두 포함한 순비용을 최소화하는 비선형 최적화 모형이고, 하위 사용자 모형은 가변수요와 용량제약으로 인한 노선의 혼잡, 그리고 노선 간환승에 따른 지체를 고려한 확률적 사용자 평형수단/경로선택 모형이다. 모형의 해법으로는 상위 모형의 경우 목적함수의 그레디언트를 기반으로 하는 "그레디언트 투사 해법"을 제안하였고, 하위모형의 경우는 기존의 "반복조정해법"을 활용하였다. 또한, 구축된 모형과 해법을 소규모 예제네트워크에 적용하여 그 수렴성과 도출된 해를 분석하였다. 본 논문의 운행빈도 설계방법론은 노선의 운영 효율성을 진단 평가하고, 투입 차량대수 제약 하에 대중교통 운영 효율을 개선하는 방안을 마련하는 데 있어 이론적인 토대로 활용될 수 있을 것으로 기대된다.

• International Journal of Reliability and Applications
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• 제2권3호
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• pp.147-160
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• 2001

The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.

• International Journal of Precision Engineering and Manufacturing
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• 제1권2호
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• pp.105-114
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• 2000

An output feedback control (OFC) is presented for a linear stochastic system with known disturbance and applied to a flexible spacecraft for the reduction of residual vibration while allowing the natural deflection during operation. By converting the tracking problem into regulator problem, the OFC minimizes the expected value of a guadratic objective function composing of error stats which always remain on the intersection of sliding hypersurfaces. For the numerical evaluation with a flexible spacecraft, a large slewing maneuver strategy is devised with a tracking model for nominal trajectory and start-cost-stop strategy for economical maneuver in conjunction with the input shaping technique. The performance and efficacy of the proposed control scheme are illustrated with the comparison of different maneuver strategies.

• 품질경영학회지
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• 제15권1호
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• pp.55-62
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• 1987

A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between successive unit demands, as well as those between successive unit losses, are independently and identically distributed random variables having negative exponential distribution with respective parameters. We have derived the steady state probability distribution of the net inventory level assuming negative exponential delivery time under the continuous review (S-1, S) inventory policy. Also we have derived the total expected cost expression and necessary conditions to be satisfied for an optimal solution.

• 한국경영과학회지
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• 제37권3호
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.57-59
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• 2001

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model has been studied, proposed, and applied. Among those models, power pool is more popular than others. This paper assumes the power pool market structure having competitive generation sector and a new method is presented to build bidding strategy in that market. The utilities participating in the market have the perfect information on their cost and price functions, but they don't know the strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price function into discrete step function. An utility knows only his own strategy, so he estimates the other's strategy using stochastic methods. For considering these conditions, we introduce the Bayesian rules and noncooperative game theory concepts. Also additional assumptions are included for simplification of solving process. Each utility builds the strategy to maximize his own expected profit function using noncooperative Bayesian game. A numerical example is given in case study to show essential features of this approach.

• 한국항해항만학회지
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• 제47권6호
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• pp.401-409
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• 2023

본 연구에서는 선박 간 정보 교환에 기반한 분산지역탐색 알고리즘과 분산확률탐색 알고리즘의 성능을 비교, 분석하고자 한다. 분산알고리즘은 선박 간 정보 교환을 기반으로 하여 최적의 피항 경로를 탐색할 수 있는 방법이다. 분산지역탐색알고리즘은 이웃 선박 중 비용 감소가 최대가 되는 선박만이 다음 예상 위치를 바꿀 수 있도록 해당 선박이 우선권을 가진다. 분산확률탐색알고리즘은 일정 확률로 최적이 아닌 값을 탐색할 수 있도록 하여 새로운 값을 탐색할 수 있도록 한다. 선박 간 충돌 피항 실험은 원형 기반 선박 충돌 피항 모델을 활용하였다. 실험 방법은 원형에 기반하여 원의 중심에서 같은 거리에 떨어진 선박을 2척부터 50척까지 증가시키면서 분산 지역 탐색알고리즘과 분산확률탐색알고리즘을 시뮬레이션 하였다. 실험 평가 방법은 각 알고리즘의 계산 소요 시간, 항행 거리, 메시지 교환 횟수를 비교 분석하였다. 실험 결과 DSSA는 DLSA에 비해 계산시간은 25%, 항행 거리는 88%, 메시지 교환 횟수는 84%를 기록하였다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2007년도 추계 학술논문 발표대회
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• pp.109-113
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• 2007

This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.