• International Journal of CAD/CAM
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• v.6 no.1
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• pp.19-27
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• 2006

To survive in the current shipbuilding industry it is of vital importance for shipyards to achieve an optimal utilization of resources, make an achievable planning and ensure that this planning is kept. Possible problems should be eliminated before production starts and if unexpected disturbances occur in the actual production the right measures should be taken. Due to the dynamic nature of the production process, the continuous variation in products and the complexity of both, all this can hardly be achieved with conventional static planning and analysis systems. Simulation provides a solution here, since this enables the modelling and evaluation of the dynamic relations between product and production process. After a global introduction to production simulation in general and the application of simulation at the Flensburger shipyard, this paper presents a tool that has been developed to simulate the various complex assembly processes taking place at shipyards. Subsequently the simulation model for the subassembly production at Flensburger, in which this tool is applied, will be discussed.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.793-796
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• 1996

This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

• Journal of Korean Society of Forest Science
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• v.80 no.1
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• pp.9-19
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• 1991

This paper discusses the applicability of two simulation models for a ten year planning period in order to predict changing forest conditions. Two simulation models therefore were developed and applied to 3,844 ha of a national forest in Kangwondo province, which is managed by Joongbu Forest District Headquaters. Growth functions of three species were derived and used to predict the residual timber volume over time. Two alternative cutting schedules caused 10-14% difference in the residual timber volume in the end of ten year planning period. This suggests the important of correct decision-makings of forest managers in forest management planning.

• Journal of the Korea Safety Management & Science
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• v.11 no.4
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• pp.193-199
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• 2009

Recently, an industrial production-distribution planning problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area is reverse logistics network. This study have developed a simulation model for the reverse logistics network. The simulation model analysis reverse logistics network issues such as inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment. Computational experiments using commercial simulation tool ARENA show that the real problems. The model can be used to decide an appropriate production-distribution planning problem in the research area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.9-17
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• 2019

In order to deal with high uncertainty and variability in emergency medical centers, many researchers have developed various models for their operational planning and scheduling. However, most of the models just provide static plans without any risk measures as their results, and thus the users often lose the opportunity to analyze how much risk the patients have, whether the plan is still implementable or how the plan should be changed when an unexpected event happens. In this study, we construct a simulation model combined with a risk-based planning and scheduling module designed by Simio LLC. In addition to static schedules, it provides possibility of treatment delay for each patient as a risk measure, and updates the schedule to avoid the risk when it is needed. By using the simulation model, the users can experiment various scenarios in operations quickly, and also can make a decision not based on their past experience or intuition but based on scientific estimation of risks even in urgent situations. An example of such an operational decision making process is demonstrated for a real mid-size emergency medical center located in Seoul, Republic of Korea. The model is designed for temporal short-term planning especially, but it can be expanded for long-term planning also with some appropriate adjustments.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.2
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• pp.33-42
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• 1983

Outage cost inclusion in operational simulation is very important subject in generation planning. Conventional discretized one in probabilistic simulation has unavoidably insufficient modeling and costly computation time. Now that the analytic operational simulation is possible, the outage cost inclusion is desired. With this inclusion the objective function of operational simulation becomes convex, so that analytic manipulation is easier. The derivation of outage cost is made in this paper, and the effects is evaluated. Further marginal cost is mentioned.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.11
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• pp.507-517
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• 2005

This paper presents the results of critical contingency analysis for the Korean power system which is performed to identify the impact of the critical contingencies on the Korean power system and set up a short term system operation planning for the purpose of preventing large scale blackout. The static and dynamic simulation is carried out for each critical contingency and the simulation results for each contingency are shown under the peak load condition for the year 2005, 2007 and 2010.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.505-511
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• 2018

Long term capacity expansion planning has to be carried out to satisfy pre-defined system reliability criterion. For purpose of assessing system reliability, probabilistic simulation technique has been widely adopted. However, the way how to approximate generator outage, especially maintenance outage, in probabilistic simulation scheme can significantly influence on reliability assessment. Therefore, in this paper, 3 different maintenance approximation methods are applied to investigate the quantitative impact of maintenance approximation method on long term capacity expansion planning.

• IE interfaces
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• v.7 no.2
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• pp.87-97
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• 1994

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involves such complicated and stochastic conditions as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method of the current system in terms of total logistics cost and driving time. This heuristics algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.182-199
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• 1996

Many vehicle routing methods have been suggested, which minimize the routing distances of vehicles to reduce the total transportation cost. But the more considerations the method takes, the higher complexites are involved in a large number of practical situations. The purpose of this paper is to develop a vehicle distribution planning system using heuristic algorithms and simulation techniques for home electronics companies. The vehicle distribution planning system developed by this study involve so complicated and stochastic conditions such as one depot, multiple nodes(demand points), multiple vehicle types, multiple order items, and other many restrictions for operating vehicles. The proposed system is compared with the nearest neighbor method and the savings method in terms of total logistics cost and driving time. This heuristic algorithm and simulation based distribution planning system is efficient in computational complexity, and give improved solutions with respect to the cost as well as the time. This method constructs a route with a minimum number of vehicles for a given demand.