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Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems (배전계통 최적 재구성 문제에 PC 클러스터 시스템을 이용한 병렬 유전 알고리즘-타부 탐색법 구현)

  • Mun Kyeong-Jun;Song Myoung-Kee;Kim Hyung-Su;Kim Chul-Hong;Park June Ho;Lee Hwa-Seok
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.53 no.10
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    • pp.556-564
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    • 2004
  • This paper presents an application of parallel Genetic Algorithm-Tabu Search(GA-TS) algorithm to search an optimal solution of a reconfiguration in distribution system. The aim of the reconfiguration of distribution systems is to determine switch position to be opened for loss minimization in the radial distribution systems, which is a discrete optimization problem. This problem has many constraints and very difficult to solve the optimal switch position because it has many local minima. This paper develops parallel GA-TS algorithm for reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10% of the population to enhance the local searching capabilities. With migration operation, best string of each node is transferred to the neighboring node aster predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium Ⅳ CPU and is connected with others through ethernet switch based fast ethernet. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution systems in the reference paper. From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution qualify. speedup. efficiency and computation time.

Parallel Genetic Algorithm-Tabu Search Using PC Cluster System for Optimal Reconfiguration of Distribution Systems

  • Mun Kyeong-Jun;Lee Hwa-Seok;Park June-Ho
    • KIEE International Transactions on Power Engineering
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    • v.5A no.2
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    • pp.116-124
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    • 2005
  • This paper presents an application of the parallel Genetic Algorithm-Tabu Search (GA- TS) algorithm, and that is to search for an optimal solution of a reconfiguration in distribution systems. The aim of the reconfiguration of distribution systems is to determine the appropriate switch position to be opened for loss minimization in radial distribution systems, which is a discrete optimization problem. This problem has many constraints and it is very difficult to solve the optimal switch position because of its numerous local minima. This paper develops a parallel GA- TS algorithm for the reconfiguration of distribution systems. In parallel GA-TS, GA operators are executed for each processor. To prevent solution of low fitness from appearing in the next generation, strings below the average fitness are saved in the tabu list. If best fitness of the GA is not changed for several generations, TS operators are executed for the upper 10$\%$ of the population to enhance the local searching capabilities. With migration operation, the best string of each node is transferred to the neighboring node after predetermined iterations are executed. For parallel computing, we developed a PC-cluster system consisting of 8 PCs. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based rapid Ethernet. To demonstrate the usefulness of the proposed method, the developed algorithm was tested and is compared to a distribution system in the reference paper From the simulation results, we can find that the proposed algorithm is efficient and robust for the reconfiguration of distribution system in terms of the solution quality, speedup, efficiency, and computation time.

High-level Autonomous Navigation Technique of AUV using Fuzzy Relational Products (퍼지관계곱을 이용한 수중운동체의 고수준 자율항행기법)

  • Lee, Young-Il;Kim, Yong-Gi
    • Journal of KIISE:Software and Applications
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    • v.29 no.1_2
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    • pp.91-97
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    • 2002
  • This paper describes a heuristic search technique carrying out collision avoidance for Autonomous Underwater Vehicles(AUVs). Fuzzy relational products are used as the mathematical implement for the analysis and synthesis of relations between obstacles that are met in the navigation environment and available candidate nodes. In this paper, we propose a more effective evaluation function that reflects the heuristic information of domain experts on obstacle clearance, and an advanced heuristic search method performing collision avoidance for AUVs. The search technique adopts fuzzy relational products to conduct path-planning of intelligent navigation system. In order to verify the performance of proposed heuristic search, it is compared with $A^*$ search method through simulation in view of the CPU time, the optimization of path and the amount of memory usage.

A Study on the Efficient Optimization Method by Coupling Genetic Algorithm and Direct Search Method (유전적 알고리즘과 직접탐색법의 결합에 의한 효율적인 최적화방법에 관한 연구)

  • D.K. Lee;S.J. Jeong;S.Y. Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.31 no.3
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    • pp.12-18
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    • 1994
  • Optimization in the engineering design is to select the best of many possible design alternatives in a complex design space. In order to optimize, various optimization methods have been used. One major problem of traditional optimization methods is that they often result in local optima. Recently genetic algorithm based on the mechanics of natural selection and natural genetics is used in many application fields for optimization. Genetic algorithm is more powerful to local optima, but it requires more calculation time and has difficulties in finding exact optimum point in design variable with real data type generally. In this paper. hybrid method was developed by coupling genetic algorithm and traditional direct search method. The developed method finds out a region for global optimum using genetic algorithm, and is to search global optimum using direct search method based on results obtained from genetic algorithm. By using hybrid method, calculation time is reduced and search efficient for optimum point is increased.

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Hybrid Genetic Algorithms for Solving Reentrant Flow-Shop Scheduling with Time Windows

  • Chamnanlor, Chettha;Sethanan, Kanchana;Chien, Chen-Fu;Gen, Mitsuo
    • Industrial Engineering and Management Systems
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    • v.12 no.4
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    • pp.306-316
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    • 2013
  • The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

Search for Ultra-faint Dwarfs in the Halo of M60, Giant Elliptical Galaxy in Virgo

  • LEE, JEONG HWAN;LEE, MYUNG GYOON;JANG, IN SUNG
    • The Bulletin of The Korean Astronomical Society
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    • v.41 no.2
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    • pp.63.2-63.2
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    • 2016
  • One of the well-known problems in the lambda cold dark matter (${\Lambda}CDM$) models is a missing satellite problem. The slope of the mass function of low mass galaxies predicted by ${\Lambda}CDM$ models is much steeper than that based on the luminosity function of dwarf galaxies in the local universe. This implies that the model prediction is an overestimate of low mass galaxies, or that the current census of dwarf galaxies in the local universe may be an underestimate of dwarf galaxies. Previous studies of galaxy luminosity functions to address this problem are based mostly on the sample of galaxies brighter than Mv ~ -10 in the nearby galaxies. In this study we try to search for ultra-faint galaxies (UFDs), which are much fainter than those in the previous studies. We use multi-field HST ACS images of M60 in the archive. M60 is a giant elliptical galaxy located in the east part of the Virgo cluster, and hosts a large population of globular clusters and UCDs. Little is known about the dwarf galaxies in this galaxy. UFDs are much fainter, much smaller, and have lower surface brightness than normal dwarf galaxies so HST images of massive galaxies are an ideal resource. We present preliminary results of this search.

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Fast Integer-Pel Motion Estimation Based on Statistical Property for H.264/AVC (H.264/AVC를 위한 통계 특성 기반 정수 화소 단위 고속 움직임 예측 기법)

  • Noh, Jin-Young;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8A
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    • pp.669-678
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    • 2012
  • In this paper, we propose an efficient fast integer-pel motion estimation for H.264/AVC using local statistics of local motion vectors. Using neighboring motion vectors, we define a new statistical property that is used to determine a mode of motion search range of current block. In addition, an adaptive motion search range compensated method that is based on cumulative statistics of previous coded blocks is addressed to solve the problem of the statistical motion search range decision method. Experimental results show that proposed algorithm has the capability to reduce the computational cost over the other methods.

An Adaptive Search Range Decision Algorithm for Fast Motion Estimation using Local Statistics of Neighboring Blocks (고속 움직임 추정을 위한 인접 블록 국부 통계 기반의 적응 탐색 영역 결정 방식)

  • 김지희;김철우;김후종;홍민철
    • Journal of Broadcast Engineering
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    • v.7 no.4
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    • pp.310-316
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    • 2002
  • In this paper, we propose an adaptive search range decision algorithm for fast motion estimation of video coding. Block matching algorithm for motion vector estimation that improves coding efficiency by reduction of temporal redundancy has trade-off problem between the motion vector accuracy and the complexity. The proposed algorithm playing as a pre-processing of fast motion estimation adaptively determines the motion search range by the local statistics of neighboring motion vectors. resulting in dramatic reduction of the computational cost without the loss of coding efficiency. Experimental results show the capability of the proposed algorithm.

Novel Method for Face Recognition using Laplacian of Gaussian Mask with Local Contour Pattern

  • Jeon, Tae-jun;Jang, Kyeong-uk;Lee, Seung-ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5605-5623
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    • 2016
  • We propose a face recognition method that utilizes the LCP face descriptor. The proposed method applies a LoG mask to extract a face contour response, and employs the LCP algorithm to produce a binary pattern representation that ensures high recognition performance even under the changes in illumination, noise, and aging. The proposed LCP algorithm produces excellent noise reduction and efficiency in removing unnecessary information from the face by extracting a face contour response using the LoG mask, whose behavior is similar to the human eye. Majority of reported algorithms search for face contour response information. On the other hand, our proposed LCP algorithm produces results expressing major facial information by applying the threshold to the search area with only 8 bits. However, the LCP algorithm produces results that express major facial information with only 8-bits by applying a threshold value to the search area. Therefore, compared to previous approaches, the LCP algorithm maintains a consistent accuracy under varying circumstances, and produces a high face recognition rate with a relatively small feature vector. The test results indicate that the LCP algorithm produces a higher facial recognition rate than the rate of human visual's recognition capability, and outperforms the existing methods.

Assessment on the Performance of Search And Rescue Service of KPS

  • Lee, Jung-Hoon;Lee, Sanguk;Won, Jong-Hoon
    • Journal of Positioning, Navigation, and Timing
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    • v.8 no.3
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    • pp.119-127
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    • 2019
  • COsmicheskaya Sisteyama Poiska Avariynich Sudov Search and Rescue Satellite-Aided Tracking (COSPAS-SARSAT) is an international communication support program to perform search and rescue (SAR) operations in emergency situations by using satellite signals relayed from a beacon. The legacy COSPAS-SARSAT was originally composed of low altitude and geostationary Earth orbit satellites; thus, a limited number of directional dish antennas was sufficient to cover the limited number of visible satellites at the local user terminal. However, the second generation COSPAS-SARSAT newly added the medium Earth orbit satellites, e.g., Global Navigation Satellite Systems (GNSS) to the existing system, so that the number of visible satellites increase dramatically, and the system upgrade to cover all the visible satellites is foreseen. The additional use of planned Korea Positioning System (KPS) to existing GNSS is envisaged to provide a better performance of their SAR service. This paper presents the benefits of the additional use of KPS together with the phased array antennas at the local user terminal of the COSPAS-SARSAT. This is to effectively response to the increase of the number of visible satellites. Numerical simulation is included to evaluate the performance improvement of COSPAS-SARSAT in terms of the number of visible satellites, geometry between satellites and user, and position estimation accuracy.