• Title/Summary/Keyword: Optimal Search Algorithm

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Optimal Path Search Algorithm for Urban Applying Received Signal Strength on Satellite Communication Environment (위성통신 환경에서 전파수신감도를 활용한 도심지 최적경로탐색 알고리즘)

  • Park, No-Uk;Kim, Joo-Seok;Lim, Joo-Yoeng;Lim, Tae-Hyuk;Yoo, Chang-Hyun;Kwon, Kun-Sup;Kim, Kyung-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.6
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    • pp.189-197
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    • 2012
  • In this paper, we propose an optimal path search algorithm that applies the received signal strength between a mobile device and a satellite. Because the common path search algorithm is only based on the shortest path search, it is difficult to provide stable multimedia services for the satellite mobile devices. The proposed algorithm provides the stable communication environment for the satellite mobile devices based on received signal strength. In Satellite communications, changes in the radio quality are severe depending on the receiving environment. Therefore, an accurate analysis of the receiving environment characteristics is very important for providing stable multimedia services of satellite communications. The causes of radio attenuation are atmosphere attenuation, vegetation attenuation and buildings attenuation. These factors were applied to analyze the received signal strength. The proposed algorithm can search the optimal path in urban for stable satellite multimedia services.

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.

Fast Motion Estimation Algorithm Using Early Detection of Optimal Candidates with Priority and a Threshold (우선순위와 문턱치를 가지고 최적 후보 조기 검출을 사용하는 고속 움직임 예측 알고리즘)

  • Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.2
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    • pp.55-60
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    • 2020
  • In this paper, we propose a fast block matching algorithm of motion estimation using early detection of optimal candidate with high priority and a threshold. Even though so many fast algorithms for motion estimation have been published to reduce computational reduction full search algorithm, still so many works to improve performance of motion estimation are being reported. The proposed algorithm calculates block matching error for each candidate with high priority from previous partial matching error. The proposed algorithm can be applied additionally to most of conventional fast block matching algorithms for more speed up. By doing that, we can find the minimum error point early and get speed up by reducing unnecessary computations of impossible candidates. The proposed algorithm uses smaller computation than conventional fast full search algorithms with the same prediction quality as the full search algorithm. Experimental results shows that the proposed algorithm reduces 30~70% compared with the computation of the PDE and full search algorithms without any degradation of prediction quality and further reduces it with other fast lossy algorithms.

An Efficient Algorithm for finding Optimal Spans to determine R=1/2 Rate Systematic Convolutional Self-Doubly Orthogonal Codes (R=1/2 Self-Doubly 조직 직교 길쌈부호를 찾는 효율적인 최적 스팬 알고리듬)

  • Doniyor, Atabaev;Suh, Hee-Jong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.11
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    • pp.1239-1244
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    • 2015
  • In this paper, a new method for finding optimal and short span in Convolutional Self-Doubly Orthogonal(CDO) codes are proposed. This new algorithm based on Parallel Implicitly-Exhaustive search, where we applied dynamic search space reduction methods in order to reduce computational time for finding Optimal Span for R=1/2 rate CDO codes. The simulation results shows that speedup and error correction performance of the new algorithm is better.

Correspondence Search Algorithm for Feature Tracking with Incomplete Trajectories

  • Jeong, Jong-Myeon;Moon, young-Shik
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.803-806
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    • 2000
  • The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

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Partial Transmit Sequence Optimization Using Improved Harmony Search Algorithm for PAPR Reduction in OFDM

  • Singh, Mangal;Patra, Sarat Kumar
    • ETRI Journal
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    • v.39 no.6
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    • pp.782-793
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    • 2017
  • This paper considers the use of the Partial Transmit Sequence (PTS) technique to reduce the Peak-to-Average Power Ratio (PAPR) of an Orthogonal Frequency Division Multiplexing signal in wireless communication systems. Search complexity is very high in the traditional PTS scheme because it involves an extensive random search over all combinations of allowed phase vectors, and it increases exponentially with the number of phase vectors. In this paper, a suboptimal metaheuristic algorithm for phase optimization based on an improved harmony search (IHS) is applied to explore the optimal combination of phase vectors that provides improved performance compared with existing evolutionary algorithms such as the harmony search algorithm and firefly algorithm. IHS enhances the accuracy and convergence rate of the conventional algorithms with very few parameters to adjust. Simulation results show that an improved harmony search-based PTS algorithm can achieve a significant reduction in PAPR using a simple network structure compared with conventional algorithms.

A Study on the Optimal Trajectory Planning for a Ship Using Genetic algorithm (유전 알고리즘을 이용한 선박의 최적 항로 결정에 관한 연구)

  • 이병결;김종화;김대영;김태훈
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.255-255
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    • 2000
  • Technical advance of electrical chart and cruising equipment make it possible to sail without a man. It is important to decide the cruising route in view of effectiveness and stability of a ship. So we need to study on the optimal trajectory planning. Genetic algorithm is a strong optimization algorithm with adaptational random search. It is a good choice to apply genetic algorithm to the trajectory planning of a ship. We modify a genetic algorithm to solve this problem. The effectiveness of the revised genetic algorithm is assured through computer simulations.

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An Optimal Sorting Algorithm for Auto IC Test Handler (IC 테스트 핸들러의 최적분류 알고리즘 개발)

  • 김종관;최동훈
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.10
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    • pp.2606-2615
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    • 1994
  • Sorting time is one of the most important issues for auto IC test handling systems. In actual system, because of too much path, reducing the computing time for finding a sorting path is the key way to enhancing the system performance. The exhaustive path search technique can not be used for real systems. This paper proposes heuristic sorting algorithm to find the minimal sorting time. The suggested algorithm is basically based on the best-first search technique and multi-level search technique. The results are close to the optimal solutions and computing time is greately reduced also. Therefore the proposed algorthm can be effectively used for real-time sorting process in auto IC test handling systems.

A Novel Region Decision Method with Mesh Adaptive Direct Search Applied to Optimal FEA-Based Design of Interior PM Generator

  • Lee, Dongsu;Son, Byung Kwan;Kim, Jong-Wook;Jung, Sang-Yong
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1549-1557
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    • 2018
  • Optimizing the design of large-scale electric machines based on nonlinear finite element analysis (FEA) requires longer computation time than other applications of FEA, mainly due to the huge size of the machines. This paper addresses a new region decision method (RDM) with mesh adaptive direct search (MADS) for the optimal design of wind generators in order to reduce the computation time. The validity of the proposed algorithm is evaluated using Rastrigin and Goldstein-Price benchmark function. Moreover, the algorithm is employed for the optimal design of a 5.6MW interior permanent magnet synchronous generator to minimize the torque ripple. Additionally, mechanical stress analysis as well as electromagnetic field analysis have been implemented to prevent breakdown caused by large centrifugal forces of the modified design.