• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.1114-1116
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• 2005

Shop floor control systems (SFCS) are used to make real-time planning and scheduling decisions to optimize the efficiency of manufacturing shops. These shops exhibit a non-linear, dynamic evolution caused by 1) the concurrent flows of disparate parts following complex routings, 2) a variety of machines that breakdown at random times, 3) stochastic arrivals of new parts with different priorities, and 4) jobs that have probabilistic processing times and transportation times. Because of their ability to capture that evolution faithfully, simulation models are often used in the aforementioned decisions. In this paper, various types of decision-making problems encountered in a shop floor have been investigated and categorized into process related problems and resource related problems for shop floor simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.328-333
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• 2007

Traditional maintenance planning is based on a constant maintenance interval for equipment life. In order to consider economic aspect for tm based preventive maintenance, preventive maintenance is desirable to be scheduled by RCM(Reliability-Centered Maintenance) evaluation. The main objective of RCM is to reduce the maintenance cost, by focusing on the most important functions of the system and avoiding or removing maintenance actions that are not strictly necessary. So, Markov state model is utilized considering stochastic state in RCM In this paper, a Markov state model much can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by the stepwise Markov model in detail. Also, because the system is not continuously monitored, the inspection is considered. In case study, simulation results about RCM will be shown using the real historical data of combustion turbine generating unit in Korean power systems.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.357-359
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• 2006

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1021-1035
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• 2008

In this paper, we analyze an N-design call center with skill-based routing, in which one pool of agents handles two types of calls and another pool of agents handles only one type of calls. The approximate analysis is motivated by a computational complexity that has been observed in the direct stochastic approach and numerical method for finding performance measures. The workforce staffing policy is very important to the successful management of call centers. So the allocation scheduling of the agents can be considered as the optimization problem of the corresponding queueing system to the call center. We use a decomposition algorithm which divides the state space of the queueing system into the subspaces for the approximate analysis of the N-design call center with two different types of agents. We also represent some numerical examples and show the impact of the system parameters on the performance measures.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.248-253
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• 2007

Traditional time based preventive maintenance is used to constant maintenance interval for equipment life. In order to consider economic aspect for time based preventive maintenance, preventive maintenance is scheduled by RCM(Reliability-Centered Maintenance) evaluation. So, Markov state model is utilized considering stochastic state in RCM. In this paper, a Markov state model which can be used for scheduling and optimization of maintenance is presented. The deterioration process of system condition is modeled by a Markov model. In case study, simulation results about RCM are used to the real historical data of combustion turbine generating units in Korean power systems.

• Journal of the Korean Mathematical Society
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• v.47 no.1
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• pp.17-28
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• 2010

In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.3 no.3
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• pp.13-22
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• 1980

Research and Development has a property that involves uncertainity and risk in itself. Therefore, in order to scheduling of R & D activity, it Is needed of a certain probabilistic network technique with due regard to feedback process used to occur in the R & D proceeding. It is GERT that was developed as the need arises . In this study, the network structure of GERT-I and GERT-II was combined and then simulation analysis was used to it. According to that analysis , an advanced GERT model which covers the following stochastic problems was examined. 1 Evaluating success feasibility under the complex condition (time and cost). 2 Selecting acceptance range for the worst. 3. Selecting optimum path on basis of time, cost and success. 4. Evaluating project utility among the project alternatives. It is for managing R&D projects more effectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.16-23
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• 2011

이 논문에서는 지진이나 해일과 같은 자연재해가 발생했을 때 생존자의 수를 최대화하기 위한 응급차량의 배차 문제에 대하여 살펴본다. 이 경우에는 도로 네트워크상에서 최단거리에 있으리라 예상되는 환자부터 실어 나르는 스케줄링 규칙을 많이 이용한다. 이 스케줄링 규칙을 SEPT(Shortest Expected Processing Time) 라고 한다. 이 논문에서는 SEPT보다 효율적이라 생각되는 새로운 스케줄링 규칙을 제안한다. 이 스케줄링 규칙은 처리시간과 납기일이 확정적인 경우에 생존자의 수를 최대화시켜주는 스케줄링을 제공하는 Moore의 알고리즘을 처리시간과 납기일이 확률적인 경우로 확장한 것이다. 다음으로 이 스케줄링 규칙을 지진이 많이 발생하는 미국 캘리포니아 주 로스앤젤레스의 한 지역을 대상으로 몇 가지 생존확률 하에서 생존자의 수를 기준으로 SEPT와 비교한다. 그 결과 모든 생존확률 하에서 제안된 스케줄링 규칙이 SEPT보다 평균적으로 생존자의 수를 더 늘려주는 스케줄링을 제공한다. 그리고 많은 경우 제안된 스케줄링 규칙은 최적 스케줄링을 제공한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05b
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• pp.159-162
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• 2009

Today's construction is more various and more complex. Because of that, a lot of uncertain factors are occurred and they related uncertain construction duration. For management complex architecture project, importance of construction schedule management also increased. In previous studies, one of solutions to overcome those problems is suggested. It was BIM based construction simulation process which focused on construction schedule and construction schedule management. But latest process had limited point which has no duration estimation function. So this paper suggested duration estimation method and developed duration estimation module. Duration estimation module developed with current scheduling tool MS Project and their macro function. However, this module has just developed Reinforced Concrete Structure and has to do more development and research.