• 제목/요약/키워드: Simulated annealing method

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GA와 SA 알고리듬의 조합을 이용한 최적의 BPCGH의 설계 (Design of optimal BPCGH using combination of GA and SA Algorithm)

  • 조창섭;김철수;김수중
    • 한국통신학회논문지
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    • 제28권5C호
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    • pp.468-475
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    • 2003
  • 본 논문에서는 패턴생성을 위한 최적의 이진 위상 컴퓨터형성 홀로그램을 설계하기 위해 합성된 SA알고리듬 및 유전 알고리듬을 이용하였다. 제안된 방법의 탐색과정에서 sGA를 사용하여 BPCGH를 생성하고. 결과 홀로그램 패턴을 SA 알고리듬의 초기 랜덤 투과함수로 이용하여 최적의 BPCGH를 설계하였다. 컴퓨터 시뮬레이션에서 독립적으로 사용된 SA 알고리듬과 유전 알고리듬을 비교한 결과 제안한 알고리듬이 회절 효율이 향상된 것을 확인할 수 있었다.

데이터 클러스터링을 위한 혼합 시뮬레이티드 어닐링 (Hybrid Simulated Annealing for Data Clustering)

  • 김성수;백준영;강범수
    • 산업경영시스템학회지
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    • 제40권2호
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    • pp.92-98
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    • 2017
  • Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

Optimized Local Relocation for VLSI Circuit Modification Using Mean-Field Annealing

  • Karimi, Gholam Reza;Verki, Ahmad Azizi;Mirzakuchaki, Sattar
    • ETRI Journal
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    • 제32권6호
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    • pp.932-939
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    • 2010
  • In this paper, a fast migration method is proposed. Our method executes local relocation on a model placement where an additional module is added to it for modification with a minimum number of displacements. This method is based on mean-field annealing (MFA), which produces a solution as reliable as a previously used method called simulated annealing. The proposed method requires substantially less time and hardware, and it is less sensitive to the initial and final temperatures. In addition, the solution runtime is mostly independent of the size and complexity of the input model placement. Our proposed MFA algorithm is optimized by enabling module rotation inside an energy function called permissible distances preservation energy. This, in turn, allows more options in moving the engaged modules. Finally, a three-phase cooling process governs the convergence of problem variables called neurons or spins.

비선형모형에서 최적실험계획법의 계산에 관한 연구 - 시뮬레이티드 어닐링 알고리듬의 응용 - (Computational Methods for Optimal Designs In Nonlinear Models using the Simulated Annealing Algorithm)

  • 강명욱
    • 품질경영학회지
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    • 제24권4호
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    • pp.59-69
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    • 1996
  • The criteria for construction of D-optimal design in nonlinear models are derived. The procedures for finding these optimal designs using the simulated annealing algorithm are presented. It is claimed that the advantages of this method are its ability to make the given data useful by adding new observations as well as to obtain a new set of appropriate data when the model and parameters are known. Research so far indicates that there has never been a case in which there is more than one independent variable but this method can be used for such cases. The result indicates the effectiveness of the method using simulated annealing algorithm for situations in which there are many independent variables and the ranges of design spaces are wide.

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적층 쾌속조형 시스템을 위한 시뮬레이티드 어닐링 경사절단 알고리즘 (A Simulated Annealing Tangential Cutting Algorithm for Lamination Rapid Prototyping System)

  • 김명숙;엄태준;김승우;천인국;공용해
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권4호
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    • pp.226-234
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    • 2004
  • A rapid Prototyping system that laser-cuts and laminates thick layers can fabricate 3D objects promptly with a variety of materials. Building such a system must consider the surface distortions due to both vertical-cut layers and triangular surfaces. We developed a tangential layer-cutting algorithm by rearranging tangential lines such that they reconstruct 3D surfaces more closely and also constitute smoother laser trajectories. An energy function that reflects the surface-closeness with the tangential lines was formulated and then the energy was minimized by a gradient descent method. Since this simple method tends to cause many local minima for complex 3D objects, we tried to solve this problem by adding a simulated annealing process to the proposed method. To view and manipulate 3D objects, we also implemented a 3D visual environment. Under this environment, experiments on various 3D objects showed that our algorithm effectively approximates 3D surfaces and makes laser-trajectory feasibly smooth.

초분광 영상 특징선택과 밴드비 기법을 이용한 유사색상의 특이재질 검출기법 (Specific Material Detection with Similar Colors using Feature Selection and Band Ratio in Hyperspectral Image)

  • 심민섭;김성호
    • 제어로봇시스템학회논문지
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    • 제19권12호
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    • pp.1081-1088
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    • 2013
  • Hyperspectral cameras acquire reflectance values at many different wavelength bands. Dimensions tend to increase because spectral information is stored in each pixel. Several attempts have been made to reduce dimensional problems such as the feature selection using Adaboost and dimension reduction using the Simulated Annealing technique. We propose a novel material detection method that consists of four steps: feature band selection, feature extraction, SVM (Support Vector Machine) learning, and target and specific region detection. It is a combination of the band ratio method and Simulated Annealing algorithm based on detection rate. The experimental results validate the effectiveness of the proposed feature selection and band ratio method.

능동방음벽 시스템의 제어 음원 위치 선정에 미치는 최적화 기법 성능 비교 연구 (A Study on the Performance Comparison of Optimization Techniques on the Selection of Control Source Positions in an Active Noise Barrier System)

  • 임형진;백광현
    • 한국소음진동공학회논문집
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    • 제15권8호
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    • pp.911-917
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    • 2005
  • There were many attempts to reduce noise behind the noise barrier using active control techniques. Omoto(1993) Shao(1997) and Yang(2001) tried to actively control the diffracted noise behind the barrier and main concerns were about the arrangement methods for the control sources. Baek (2004) tried to get better results using the simulated annealing method and the sequential searching technique. The main goal of this study is to develop and compare the performance of several optimization techniques including those mentioned above, hybrid version of simulated annealing and genetic algorithm for the optimal control source positions of active noise barrier system. The simulation results show fairly similar performance lot the small size of searching problem. However, as the number of control sources are increased, the performance of simulated annealing algorithm and genetic algorithm are better than the others. Simulations are also made to show the performance of the selected optimal control source positions not only at the receiver position but at the surrounding volume of the receiver position and plotted the noise reduction level in 3-D.

조립라인의 밸런싱을 고려한 자동 조립 순서 추론 (Generation of Robotic Assembly Aequences with Consideration of Line Balancing Using a Simulated Annealing)

  • 홍대선;조형석
    • 제어로봇시스템학회논문지
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    • 제1권2호
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    • pp.112-118
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    • 1995
  • In designing assembly lines, it is required that the lines should not only meet the demand of the product, but also minimize the assembly cost associated with the line. For such a purpose, numerous research efforts have been made on either the assembly sequence generation or the assembly line balancing. However, the works dealing with both the research problems have been seldom reported in literature. When assembly sequences are generated without consideration of line balancing, additional cost may be incurred, because the sequences may not guarantee the minimum number of workstations. Therefore, it is essential to consider line balancing in the generation of cost-effective assembly sequences. To incorporate the two research problems into one, this paper treats a single-model and deterministic (SMD) assembly line balancing (ALB) problem, and proposes a new method for generating line-balanced robotic assembly sequences by using a simulated annealing. In this method, an energy function is derived in consideration of the satisfaction of assembly constraints, and the minimization of both the assembly cost and the idle time. Then, the energy function is iteratively minimized and occasionally perturbed by the simulated annealing. When no further change in energy occurs, an assembly sequence with consideration of line balancing is finally found. To show the effectiveness of the proposed scheme, a case study for an electrical relay is presented.

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MIN의 최적경로 배정을 위한 신경회로망 알고리즘의 비교 (Comparison of neural network algorithms for the optimal routing in a Multistage Interconnection Network)

  • 김성수;공성곤
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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    • pp.569-571
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    • 1995
  • This paper compares the simulated annealing and the Hopfield neural network method for an optimal routing in a multistage interconnection network(MIN). The MIN provides a multiple number of paths for ATM cells to avoid cell conflict. Exhaustive search always finds the optimal path, but with heavy computation. Although greedy method sets up a path quickly, the path found need not be optimal. The simulated annealing can find an sub optimal path in time comparable with the greedy method.

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시뮬레이티드 어닐링 알고리듬의 강건설계 : 혼합모델 투입순서 결정문제에 대한 적용 (A Robust Design of Simulated Annealing Approach : Mixed-Model Sequencing Problem)

  • 김호균;백천현;조형수
    • 산업공학
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    • 제15권2호
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    • pp.189-198
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    • 2002
  • Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.