• 한국시뮬레이션학회논문지
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• 제9권4호
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• pp.1-10
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• 2000

One of the primary goals of the simulation experiments is to understand the overall system behavior and to analyze the system, ultimately to optimize the system. Optimizing the system includes determining the optimum condition of the system parameters of interest. This paper is concerned with the simulation methodology for estimating the unknown objective function for the system of interest and optimizing the system with respect to the controllable factors. In the process of estimating the unknown objective function, which is assumed to be a second order spline function, we use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. We will show some mathematical result for the benefit of using common random numbers.

• 한국시뮬레이션학회논문지
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• 제10권4호
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• pp.41-50
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• 2001

When optimizing a complex system by determining the optimum condition of the system parameters of interest, we often employ the process of estimating the unknown objective function, which is assumed to be a second order spline function. In doing so, we normally use common random numbers for different set of the controllable factors resulting in more accurate parameter estimation for the objective function. In this paper, we will show some mathematical result for the analysis of variance when using common random numbers in terms of the regression error, the residual error and the pure error terms. In fact, if we can realize the special structure of the covariance matrix of the error terms, we can use the result of analysis of variance for the uncorrelated experiments only by applying minor changes.

• 한국생물공학회:학술대회논문집
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• 한국생물공학회 2003년도 생물공학의 동향(XIII)
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• pp.105-105
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• 2003

• 대한산업공학회지
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• 제13권1호
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• pp.61-67
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• 1987

A tool for optimizing simulated discrete variable stochastic systems, SIMICOM was developed and presented in [5]. In this paper an evaluation of its performance and results of comparisons with other popular methods for dealing with simulation-optimization problems will be provided. Based on several test problems it is concluded that SIMICOM dominates those methods.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
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• pp.250.1-250.1
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• 2014

A multicusp ion source has been used widely in negative hydrogen cyclotrons mainly for radioisotope productions. The ion source is designed to have cusp geometries of magnetic field inside plasma chamber, where ions are confining and their mean lifetimes increase. The magnetic confinement produced a number of permanent magnetic poles helps to increase beam currents and reduce the emittance. Therefore optimizing the number of magnets confining more ions and increasing their mean lifetime in plasma has to be investigated in order to improve the performance of the ion source. In this work a numerical simulation of the magnetic flux density from a number of permanent magnets is carried to optimize the cusp geometries producing the highest plasma density, which is clearly indicated along the full-line cusp geometry. The effect of magnetic fields and a number of poles on the plasma structure are investigated by a computing tool. The electron confinement effect becomes stronger and the density increases with increasing the number of poles. On the contrary, the escape of electrons from the loss cone becomes more frequent as the pole number increases [1]. To understand above observation the electron and ion's trajectories along with different cusp geometries are simulated. The simulation has been shown that the optimized numbers of magnets can improve the ion density and uniformity.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.405-424
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• 2001

Many simulation models have been built to facilitate simulation technique in designing, evaluating, and optimizing supply chains. Simulation is preferred to deal with stochastic natures existing in the supply chain. Moreover simulation has a capability to find local optimum value within each component through entire supply chain. Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event and continuous simulation is provoked, resulting in a combined discrete-continuous simulation. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which includes the equation of continuous portion in supply chain and how these equations are used in the supply chain simulation models. A simple example of supply chain model dealing with the strategic level of supply chain presented in this paper shows the possibility and the prospect of this approach.

• 한국시뮬레이션학회논문지
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• 제10권2호
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• pp.75-89
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• 2001

Many simulation models have been built to facilitate simulation technique in designing, evaluating, and optimizing supply chains. Simulation is preferred to deal with stochastic natures existing in the supply chain. Moreover simulation has a capability to find local optimum value within each component through entire supply chain. Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event and continuous simulation is provoked, resulting in a combined discrete-continuous simulation. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which includes the equation of continuous portion in supply chain and how these equations are used in the supply chain simulation models. A simple example of supply chain model dealing with the strategic level of supply chain presented in this paper shows the possibility and the prospect of this approach.

• ETRI Journal
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• 제44권2호
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• pp.313-326
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• 2022

This study presents a noble scheme for distributed and parallel simulations with optimized agent placement for simulation instances. The traditional parallel simulation has some limitations in that it does not provide sufficient performance even though using multiple resources. The main reason for this discrepancy is that supporting parallelism inevitably requires additional costs in addition to the base simulation cost. We present a comprehensive study of parallel simulation architectures, execution flows, and characteristics. Then, we identify critical challenges for optimizing large simulations for parallel instances. Based on our cost-benefit analysis, we propose a novel approach to overcome the performance constraints of agent-based parallel simulations. We also propose a solution for eliminating the synchronizing cost among local instances. Our method ensures balanced performance through optimal deployment of agents to local instances and an adaptive agent placement scheme according to the simulation load. Additionally, our empirical evaluation reveals that the proposed model achieves better performance than conventional methods under several conditions.

• 전기학회논문지
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• 제59권12호
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• pp.2157-2164
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• 2010

Microgrid is generally defined as cluster of small distributed generators, energy storages and loads. Through monitoring and coordinated control, microgrid can provide various benefits such as reduction of energy cost, peak shaving and power quality improvement. In design stage of microgrid, system dynamic simulation is necessary for optimizing of sizing and siting of DER(distributed energy resources). As number of the system components increases, simulation time will be longer. This problem can restrict optimal design. So we used simplified modeling on energy sources and average switching model on power converters to reduce simulation time. The effectiveness of this method is verified by applying to prototype microgrid system, which is consist of photovoltaic, wind power, diesel engine generators, battery energy storage system and loads installed in laboratory. Simulation by Matlab/Simulink and measurements on prototype microgrid show that the proposed method can reduce simulation time not sacrificing dynamic characteristics.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 12th Asian Congress of Fluid Mechanics
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• pp.42.6-43
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• 2008