• Title/Summary/Keyword: Simulated Annealing (SA)

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Performance Improvement on MFCM for Nonlinear Blind Channel Equalization Using Gaussian Weights (가우시안 가중치를 이용한 비선형 블라인드 채널등화를 위한 MFCM의 성능개선)

  • Han, Soo-Whan;Park, Sung-Dae;Woo, Young-Woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.407-412
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    • 2007
  • 본 논문에서는 비선형 블라인드 채널등화기의 구현을 위하여 가우시안 가중치(gaussian weights)를 이용한 개선된 퍼지 클러스터(Modified Fuzzy C-Means with Gaussian Weights: MFCM_GW) 알고리즘을 제안한다. 제안된 알고리즘은 기존 FCM 알고리즘의 유클리디언 거리(Euclidean distance) 값 대신 Bayesian Likelihood 목적함수(fitness function)와 가우시안 가중치가 적용된 멤버쉽 매트릭스(partition matrix)를 이용하여, 비선형 채널의 출력으로 수신된 데이터들로부터 최적의 채널 출력 상태 값(optimal channel output states)들을 직접 추정한다. 이렇게 추정된 채널 출력 상태 값들로 비선형 채널의 이상적 채널 상태(desired channel states) 벡터들을 구성하고, 이를 Radial Basis Function(RBF) 등화기의 중심(center)으로 활용함으로써 송신된 데이터 심볼을 찾아낸다. 실험에서는 무작위 이진 신호에 가우시안 잡음이 추가된 데이터를 사용하여 기존의 Simplex Genetic Algorithm(GA), 하이브리드 형태의 GASA(GA merged with simulated annealing (SA)), 그리고 과거에 발표되었던 MFCM 등과 그 성능을 비교 분석하였으며, 가우시안 가중치가 적용된 MFCM_GW를 이용한 채널등화기가 상대적으로 정확도와 속도 면에서 우수함을 보였다.

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Development of a Heuristic Method for Solving a Class of Nonlinear Integer Programs with Application to Redundancy Optimization for the Safely Control System using Multi-processor (비선형정수계획의 새로운 발견적해법의 개발과 고성능 다중프로세서를 이용한 안전관리 시스템의 신뢰도 중복설계의 최적화)

  • 김장욱;김재환;황승옥;박춘일;금상호
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.1 no.2
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    • pp.69-82
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    • 1995
  • This study is concerned with developing a heuristic algorithm for solving a class of ninlinear integer programs(NLIP). Exact algrithm for solving a NLIP either may not exist, or may take an unrealistically large amount of computing time. This study develops a new heuristic, the Excursion Algorithm(EA), for solving a class of NLIP's. It turns out that excursions over a bounded feasible and/or infeasible region is effective in alleviation the risks of being trapped at a lical optimum. The developed EA is applied to the redundancy optimization problems for improving the system safety, and is compared with other existing heuristic methods. We also include simulated annealing(SA) method in the comparision experiment due to ist populatrity for solving complex combinatorial problems. Computational results indicate that the proposed EA performs consistently better than the other in terms of solution quality, with moderate increase in computing time. Therefore, the proposed EA is believed to be an attractive alternative to other heuristic methods.

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A Hybrid Parallel Genetic Algorithm for Reliability Optimal Design of a Series System (직렬시스템의 신뢰도 최적 설계를 위한 Hybrid 병렬 유전자 알고리즘 해법)

  • Kim, Ki-Tae;Jeon, Geon-Wook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.33 no.2
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    • pp.48-55
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    • 2010
  • Reliability has been considered as a one of the major design measures in various industrial and military systems. The main objective is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for the problem that determines the optimal component reliability to maximize the system reliability under cost constraint in this study. Reliability optimization problem has been known as a NP-hard problem and normally formulated as a mixed binary integer programming model. Component structure, reliability, and cost were computed by using HPGA and compared with the results of existing meta-heuristic such as Ant Colony Optimization(ACO), Simulated Annealing(SA), Tabu Search(TS) and Reoptimization Procedure. The global optimal solutions of each problem are obtained by using CPLEX 11.1. The results of suggested algorithm give the same or better solutions than existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improving solution through swap and 2-opt processes.

Bayesian Nonlinear Blind Channel Equalizer based on Gaussian Weighted MFCM

  • Han, Soo-Whan;Park, Sung-Dae;Lee, Jong-Keuk
    • Journal of Korea Multimedia Society
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    • v.11 no.12
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    • pp.1625-1634
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    • 2008
  • In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for the problem of nonlinear blind channel equalization. The proposed algorithm searches for the optimal channel output states of a nonlinear channel based on received symbols. In contrast to conventional Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in this method. In the search procedure, all possible sets of desired channel states are constructed by considering the combinations of estimated channel output states. The set of desired states characterized by the maxima] value of the Bayesian fitness is selected and updated by using the Gaussian weights. After this procedure, the Bayesian equalizer with the final desired states is implemented to reconstruct transmitted symbols. The performance of the proposed method is compared with those of a simplex genetic algorithm (GA), a hybrid genetic algorithm (GA merged with simulated annealing (SA):GASA), and a previously developed version of MFCM. In particular, a relative]y high accuracy and a fast search speed have been observed.

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Analysis for Applicability of Differential Evolution Algorithm to Geotechnical Engineering Field (지반공학 분야에 대한 차분진화 알고리즘 적용성 분석)

  • An, Joon-Sang;Kang, Kyung-Nam;Kim, San-Ha;Song, Ki-Il
    • Journal of the Korean Geotechnical Society
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    • v.35 no.4
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    • pp.27-35
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    • 2019
  • This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

Comparison of Optimal Path Algorithms and Implementation of Block Transporter Planning System (최적 경로 알고리즘들의 계산비용 비교 및 트랜스포터의 최적 블록 운송 계획 적용)

  • Moon, Jong-Heon;Ruy, Won-Sun;Cha, Ju-Hwan
    • Journal of the Society of Naval Architects of Korea
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    • v.53 no.2
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    • pp.115-126
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    • 2016
  • In the process of ship building, it is known that the maintenance of working period and saving cost are one of the important part during the logistics of blocks transportation. Precise operational planning inside the shipyard plays a big role for a smooth transportation of blocks. But many problems arise in the process of block transportation such as the inevitable road damage during the transportation of the blocks, unpredictable stockyard utilization of the road associated with a particular lot number, addition of unplanned blocks. Therefore, operational plan needs to be re-established frequently in real time for an efficient block management. In order to find the shortest path between lot numbers, there are several representative methods such as Floyd algorithm that has the characteristics of many-to-many mapping, Dijkstra algorithm that has the characteristic of one-to-many mapping, and the A* algorithm which has the one-to-one mapping, but many authors have published without the mutual comparisons of these algorithms. In this study, some appropriate comparison have been reviewed about the advantages and disadvantages of these algorithms in terms of precision and cost analysis of calculating the paths and planning system to operate the transporters. The flexible operating plan is proposed to handle a situation such as damaged path, changing process during block transportation. In addition, an operational algorithm of a vacant transporter is proposed to cover the shortest path in a minimum time considering the situation of transporter rotation for practical use.

Development of New Meta-Heuristic For a Bivariate Polynomial (이변수 다항식 문제에 대한 새로운 메타 휴리스틱 개발)

  • Chang, Sung-Ho;Kwon, Moonsoo;Kim, Geuntae;Lee, Jonghwan
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.2
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    • pp.58-65
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    • 2021
  • Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

Three-Dimensional Image Display System using Stereogram and Holographic Optical Memory Techniques (스테레오그램과 홀로그래픽 광 메모리 기술을 이용한 3차원 영상 표현 시스템)

  • 김철수;김수중
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.6B
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    • pp.638-644
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    • 2002
  • In this paper, we implemented a three dimensional image display system using stereogram and holographic optical memory techniques which can store many images and reconstruct them automatically. In this system, to store and reconstruct stereo images, incident angle of reference beam must be controlled in real time, so we used BPH(binary phase hologram) and LCD(liquid crystal display) for controlling reference beam. The reference beams are acquired by Fourier transform of BPHs which designed with SA(simulated annealing)algorithm, and the BPHs are represented on the LCD with the 0.05 seconds time interval using application software for reconstructing the stereo images. And input images are represented on the LCD without polarizer/analyzer for maintaining uniform beam intensities regardless of the brightness of input images. The input images and BPHs are edited using application software(Photoshop) with having the same recording scheduled time interval in storing. The reconstructed stereo images are acquired by capturing the output images with CCD camera at the behind of the analyzer which transforms phase information into brightness information of images. In output plane, we used a LCD shutter that is synchronized to a monitor that display alternate left and right eye images for depth perception. We demonstrated optical experiment which store and reconstruct four stereo images in BaTiO$_3$ repeatedly using the proposed holographic optical memory techniques.