• Industrial Engineering and Management Systems
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• 제4권2호
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• pp.184-191
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• 2005

In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of ACO on the Kanban allocation problem, and identify the most important parameters.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2016년도 제50회 동계 정기학술대회 초록집
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• pp.289.2-289.2
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• 2016

In-Ga-Zn-O(IGZO) receive great attention as a channel material for thin film transistors(TFTs) as next-generation display panel backplanes due to its superior electrical and physical properties such as a high mobility, low off-current, high sub-threshold slope, flexibility, and optical transparency. For the purpose of fabricating high performance IGZO TFTs, a thermal recovery process above a temperature of $300^{\circ}C$ is required for recovery or rearrangement of the ionic bonding structure. However diffused metal atoms from source/drain(S/D) electrodes increase the channel conductivity through the oxidation of diffused atoms and reduction of $In_2O_3$ during the thermal recovery process. Threshold voltage ($V_{TH}$) shift, one of the electrical instability, restricts actual applications of IGZO TFTs. Therefore, additional investigation of the electrical stability of IGZO TFTs is required. In this paper, we demonstrate the effect of Ti diffusion and modulation of interface traps by carrying out an annealing process on IGZO. In order to investigate the effect of diffused Ti atoms from the S/D electrode, we use secondary ion mass spectroscopy (SIMS), X-ray photoelectron spectroscopy, HSC chemistry simulation, and electrical measurements. By thermal annealing process, we demonstrate VTH shift as a function of the channel length and the gate stress. Furthermore, we enhance the electrical stability of the IGZO TFTs through a second thermal annealing process performed at temperature $50^{\circ}C$ lower than the first annealing step to diffuse Ti atoms in the lateral direction with minimal effects on the channel conductivity.

• 한국시뮬레이션학회논문지
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• 제24권4호
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• pp.77-88
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• 2015

본 논문은 작업별 위치기반 지수학습 효과를 갖는 2-에이전트 단일기계 스케줄링 문제를 고려한다. 에이전트 A는 가중 완료 시간의 합을 최소화하며, 에이전트 B는 총소요시간에 대한 상한 값을 만족하는 조건을 갖는다. 본 연구에서는 먼저 우수해/가능해에 대한 특성을 개발하고, 이를 이용하여 최적 해를 찾기 위한 분지한계 알고리즘을 설계한다. 또한 근사 최적 해를 구하기 위해 6가지 다른 초기해 생성 방법을 이용한 시뮬레이티드 어닐링 알고리즘을 제안한다. 수치 실험을 통해 제안된 알고리즘의 우수한 성능을 검증한다. 실험 결과, 다른 초기해 생성 방법들 간에는 %errors 차이가 유의하게 발생하지 않았으며, 에이전트 A의 작업 순서를 무작위로 생성할 때 성능이 좋아짐을 발견하였다. 반면에, 에이전트 B의 초기해 생성 방법은 성능에 영향을 미치지 않았다.

• 한국산학기술학회논문지
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• 제18권2호
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• pp.704-710
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• 2017

본 연구팀은 프레스 공정의 협소공간에서 작업이 가능한 6자유도 로봇을 개발하고 있으며, 본 논문은 개발된 로봇의 작업 시간을 최소화하기 위한 작업 시퀀스 최적화 방법을 제안하였다. 우선 6 자유도 로봇의 기구학을 모델링하고 작업 시간 예측 방법을 기술하였다. 그리고 작업 시퀀스 최적화를 위하여 수학적 모델을 제시하고, 이를 바탕으로 개미 집단 시스템(ant colony system), 시뮬레이트 어니일링(simulated annealing), 유전자 알고리즘(genetic algorithm)의 세 가지 최적화 방법을 적용하고 결과를 비교 분석하였다. 시뮬레이션 결과 유전자 알고리즘이 가장 좋은 결과를 보임을 확인할 수 있었으며, 계산 속도 측면에서도 가장 빨리 최적값에 수렴하였다. 또한, 개미집단시스템과 시뮬레이티드 어니일링의 경우 여러 파라미터 값들의 설정에 따라 수렴된 최적값의 편차가 비교적 큰 것에 비하여, 유전자 알고리즘은 파라미터 값에 상관없이 안정적으로 근사 최적값을 찾을 수 있었다. 마지막으로, 로봇의 작업시퀀스 최적화 방법을 시각적으로 검증하기 위하여 Mathworks 사의 Matlab과 Coppelia Robotics 사의 V-REP (virtual robot experimentation platform)를 사용한 시뮬레이션을 수행하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.286-289
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• 1991

We simulated ion implantation and annealing condition of 1 ${\mu}m$ CMOS device using process simulator, SUPREM-II. In this simulation, optimal condition of ion implantation for symmetric threshold voltage determination of PMOS and NMOS region, junction depth and sheet resistance of source/drain region, impurity profile of each region are investigated. Ion implantation dose for 3 ${\mu}m$ N-well junction depth and symmetric threshold voltage of $|0.6|{\pm}0.1$ V were $1.9E12Cm^{-2}$(for phosphorus), $1.7E122Cm^{-2}$(for boron) respectively. Also annealing condition for dopant activation are examined about $900^{\circ}C$, 30 minutes. After final process step, N-well junction, P+ S/D junction and N+ S/D junction depth are calculated 3.16 ${\mu}m$, 0.45 ${\mu}m$ and 0.25 ${\mu}m$ respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.671-686
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• 2020

Due to the long training time and high training cost of traditional surgical training methods, the emerging virtual surgical training method has gradually replaced it as the mainstream. However, the virtual surgical system suffers from poor authenticity and high computational cost problems. For overcoming the deficiency of these problems, we propose an optimized model for the local compression deformation of soft tissue. This model uses a simulated annealing algorithm to optimize the parameters of the soft tissue model to improve the authenticity of the simulation. Meanwhile, although the soft tissue deformation is divided into local deformation region and non-deformation region, our proposed model only needs to calculate and update the deformation region, which can improve the simulation real-time performance. Besides, we define a compensation strategy for the "superelastic" effect which often occurs with the mass-spring model. To verify the validity of the model, we carry out a compression simulation experiment of abdomen and human foot and compare it with other models. The experimental results indicate the proposed model is realistic and effective in soft tissue compression simulation, and it outperforms other models in accuracy and real-time performance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.608-610
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• 2004

In continuous annealing line (CAL), POSCO, the center position control (CPC) is an essential technique that renders the steel-strip to pass at the center of a roll in order to prevent the strip from skewing or breaking. The CPC algorithm currently installed on the steering roll in the heating section of CAL is to control the strip position by using the reverse phase of error from the center position, without considering the dynamics of strip horizontal movement. Such algorithm may, unfortunately, require a manual operation occasionally when the range of strip input becomes wide, causing the dynamics 0 be dominant. Other PID-type control is rarely used in automatic operation because the excess of response may occur when the discontinuous points such as welding joints pass through rolls. In this paper, we identify the CPC system by using off-line data and design a compensator for the excessive dynamics by using the adaptive inverse control. Simulation result depicts the improved reliability of the proposed CPC system.

• 한국해양공학회지
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• 제17권6호
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• pp.38-46
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• 2003

Aim of this article is to propose Micro-Genetic Simulated Annealing (${\mu}GSA$) as a hybrid metaheuristics approach to find the global optimum of nonlinear optimisation problems. This approach combines the features of modern metaheuristics such as micro-genetic algorithm (${\mu}GAs$) and simulated annealing (SA) with the general robustness of parallel exploration and asymptotic convergence, respectively. Therefore, ${\mu}GSA$ approach can help in avoiding the premature convergence and can search for better global solution, because of its wide spread applicability, global perspective and inherent parallelism. For the superior performance of the ${\mu}GSA$, the five well-know benchmark test functions that were tested and compared with the two global optimisation approaches: scatter search (SS) and hybrid scatter genetic tabu (HSGT) approach. A practical application to structural sandwich panel is also examined by optimism the weight function. From the simulation results, it has been concluded that the proposed ${\mu}GSA$ approach is an effective optimisation tool for soloing continuous nonlinear global optimisation problems in suitable computational time frame.

• 대한산업공학회지
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• 제34권1호
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• pp.98-107
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• 2008

The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.