• 전자공학회논문지D
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• 제35D권6호
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• pp.37-45
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• 1998

본 논문에서는 본 연구진이 개발 중인 INPROS 3차원 반도체 공정 시뮬레이터 시스템에 이온주입된 불순물의 과도 확산(TED, transient enhanced diffusion) 기능을 첨가하여 수행한 계산 결과를 발표한다. 실리콘 내부에 이온주입된 불순물의 재분포를 시뮬레이션하기 위하여, 먼저 몬테카를로 방법으로 이온주입 공정을 수행하였고, 유한요소법을 이용하여 확산 공정을 수행하였다. 저온 열처리 공정에서의 붕소의 과도 확산을 확인하기 위하여, 에피 성장된 붕소 에피층에 비소와 인을 이온 주입시킨 후, 750℃의 저온에서 2시간 동안 열처리 공정을 수행하였다. 3차원 INPROS 시뮬레이터의 결과와 실험적으로 측정한 SIMS 데이터와 그 결과가 일치함을 확인하였다. INPROS의 점결함 의존성 과도 증속 확산 모델과 소자 시뮬레이터인 PISCES를 이용하여 역 단채널 길이 효과(RSCE, reverse short channel effect)를 시뮬레이션하였다.

• 한국전기전자재료학회논문지
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• 제29권12호
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• pp.750-758
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• 2016

For the channel doping of shallow junction and retrograde well formation in CMOS, indium can be implanted in silicon. The retrograde doping profiles can serve the needs of channel engineering in deep MOS devices for punch-through suppression and threshold voltage control. Indium is heavier element than B, $BF_2$ and Ga ions. It also has low coefficient of diffusion at high temperatures. Indium ions can be cause the erode of wafer surface during the implantation process due to sputtering. For the ultra shallow junction, indium ions can be implanted for p-doping in silicon. UT-MARLOWE and SRIM as Monte carlo ion-implant models have been developed for indium implantation into single crystal and amorphous silicon, respectively. An analytical tool was used to carry out for the annealing process from the extracted simulation data. For the 1D (one-dimensional) and 2D (two-dimensional) diffused profiles, the analytical model is also developed a simulation program with $C^{{+}{+}}$ code. It is very useful to simulate the indium profiles in implanted and annealed silicon autonomously. The fundamental ion-solid interactions and sputtering effects of ion implantation are discussed and explained using SRIM and T-dyn programs. The exact control of indium doping profiles can be suggested as a future technology for the extreme shallow junction in the fabrication process of integrated circuits.

• 경영과정보연구
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• 제14권
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• pp.51-65
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• 2004

We consider the Fuzzy clustering which is devised for partitioning a set of objects into a certain number of groups by assigning the membership probabilities to each object. The researches carried out in this field before show that the Fuzzy clustering concept is involved so much that for a certain set of data, the main purpose of the clustering cannot be attained as desired. Thus we Propose a new objective function, named as Fuzzy-Entroppy Function in order to satisfy the main motivation of the clustering which is classifying the data clearly. Also we suggest Mean Field Annealing Algorithm as an optimization algorithm rather than the ISODATA used traditionally in this field since the objective function is changed. We show the Mean Field Annealing Algorithm works pretty well not only for the new objective function but also for the classical Fuzzy objective function by indicating that the local minimum problem resulted from the ISODATA can be improved.

• 산업경영시스템학회지
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• 제23권54호
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• pp.77-85
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• 2000

One form of job shop scheduling problem in contemporary automated manufacturing such as flexible manufacturing systems (FMS's) is presented which we call the FMS dispatching priority problem. The FMS dispatching priority problem seeks the best dispatching priority of parts and operations, and is essentially a combinatorial optimization problem. Because of the complicated mechanism of the system, the performance of a given dispatching priority must be evaluated via simulation. Simulated annealing have been applied to the problem, and it is found that appropriate parameter setting will be desirable to get good, if not the optimal, solutions within a limited amount of time under the presence of heavy computational burden due to simulation. More specifically, experiments reveal that initial temperature is the single most important factor among other parameters and factors, and that the appropriate initial temperature depends on the allowable computer time in such a way that the less time one can afford to spend, the lower the appropriate initial temperature should be.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• 인터넷정보학회논문지
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• 제6권6호
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• pp.99-106
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• 2005

멀티프로세서 시스템에서 스케줄링은 매우 중요한 부분이지만, 최적의 해를 구하는 것이 복잡하여 다양한 휴리스틱 방법들에 의한 스케줄링 알고리즘들이 제안되고 있다. 최근 유전 알고리즘을 사용한 멀티프로세서 스케줄링 알고리즘들이 제시되고 있지만, 제시된 알고리즘 대부분은 한가지만의 목적을 가지는 단순한 알고리즘이다. 본 논문에서는 유전 알고리즘을 이용한 새로운 스케줄링 알고리즘을 제시한다. 또한, 해를 구하는 과정에서 시뮬레이티드 어닐링 (simulated annealing)의 확률을 이용하여 유전 알고리즘의 성능을 개선시킨다. 제시된 알고리즘은 태스크들의 최종 수행 완료 시간 (makespan)을 최소화하는 것과 사용된 프로세서의 수를 최소화하는 두 가지의 목표를 가진다. 모의 실험을 통하여 제시된 알고리즘이 다른 알고리즘보다 최종 수행 완료 시간과 사용된 프로세서의 수에서 더 나은 결과를 보임을 확인할 수 있었다.

• 전자공학회논문지A
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• 제32A권2호
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• pp.111-119
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• 1995

In this paper, we propose an efficient SA(simulated annealing) algorithm for the synthesis of binary phase computer generated hologram. SA algorithm is a method to find the optimal solution through iterative technique. It is important that selecting cost function and parameters within this algorithm. The aplications of converentional SA algorithm to synthesize parameters within this algorithm. The applications of conventional SA algorithm to synthesize binary hologram have many problems because of inappropriate paramters and cost function. So, we propose a new cost function and a calculation technique of proper parameters required to achieve the optimal solution. Computer simulation results show that the proposed method is better than conventional method in terms of diffraction efficiency and reconstruction error. Also, we show the reconstructed images by the proposed method through optical esperiment.

• 한국통신학회논문지
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• 제21권4호
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• pp.855-868
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• 1996

In this paper, multiplhase only filter(MPOFs) are designed using simulated annealing algorithm. These filters have excellent recognition characteristics for similar patterns or rotated patterns and enhance optical efficiency as well as spatial-bandwidth product by deleting mirror image. As the result of computer simulation to certify recogntion characteristics of similar patterns, simulated annealing-MPOF(SA-MPOF) has superior discrimination and higher correlation peak values than cosine binary phase only filters(CBPOF) and simpulated annealing-BPOF (SA-BPOF). THe filter having training process for rotated patterns of arbitraty possible angle can overcome that phase only filter(POF) and CBPOF can't recognize rotated input patterns.

• 전자공학회논문지A
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• 제31A권9호
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• pp.64-71
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• 1994

In this study, optimizing BPOFs are encoded by Simulated Annealing algorithm that is widely used among the optimization algorithms. Two BPOFs are trained by digit patterns, 0~9, and the digits each having 4 intraclass patterns are multiplexed. When each digit is encoded by four bit binary code, from the results of computer simulation, the correlation pezk is shown at binary value 1 position among the spatially separated four positions at the correlation plane And then, the designed BPOFs are implemented by CGH technique. Through the optical correlation experiment, satisactory results are achieved, inspite of some experimental errors and information loss owing to the amplitude type CGH filter.

• 산업공학
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• 제21권3호
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• pp.254-261
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• 2008

Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.