• Title/Summary/Keyword: Optimal Search Algorithm

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Fast Search Algorithm for Determining the Optimal Number of Clusters using Cluster Validity Index (클러스터 타당성 평가기준을 이용한 최적의 클러스터 수 결정을 위한 고속 탐색 알고리즘)

  • Lee, Sang-Wook
    • The Journal of the Korea Contents Association
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    • v.9 no.9
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    • pp.80-89
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    • 2009
  • A fast and efficient search algorithm to determine an optimal number of clusters in clustering algorithms is presented. The method is based on cluster validity index which is a measure for clustering optimality. As the clustering procedure progresses and reaches an optimal cluster configuration, the cluster validity index is expected to be minimized or maximized. In this Paper, a fast non-exhaustive search method for finding the optimal number of clusters is designed and shown to work well in clustering. The proposed algorithm is implemented with the k-mean++ algorithm as underlying clustering techniques using CB and PBM as a cluster validity index. Experimental results show that the proposed method provides the computation time efficiency without loss of accuracy on several artificial and real-life data sets.

A study on path planning and avoidance of obstacle for mobile robot by using genetic algorithm (유전알고리즘을 이용한 이동로봇의 경로계획 및 충돌회피에 관한 연구)

  • 김진수;이영진;이권순
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1193-1196
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    • 1996
  • Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

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Optimal Setting of Overcurrent Relay in Distribution Systems Using Adaptive Evolutionary Algorithm (적응진화연산을 이용한 배전계통의 과전류계전기 최적 정정치 결정)

  • Jeong, Hee-Myung;Lee, Hwa-Seok;Park, June-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.9
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    • pp.1521-1526
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    • 2007
  • This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

Optimal Design of a Hybrid Structural Control System using a Self-Adaptive Harmony Search Algorithm (자가적응 화음탐색 알고리즘을 이용한 복합형 최적 구조제어 시스템 설계)

  • Park, Wonsuk
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.31 no.6
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    • pp.301-308
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    • 2018
  • This paper presents an optimal design method of a hybrid structural control system considering multi-hazard. Unlike a typical structural control system in which one system is designed for one specific type of hazard, a simultaneous optimal design method for both active and passive control systems is proposed for the mitigation of seismic and wind induced vibration responses of structures. As a numerical example, an optimal design problem is illustrated for a hybrid mass damper(HMD) and 30 viscous dampers which are installed on a 30 story building structure. In order to solve the optimization problem, a self-adaptive Harmony Search(HS) algorithm is adopted. Harmony Search algorithm is one of the meta-heuristic evolutionary methods for the global optimization, which mimics the human player's tuning process of musical instruments. A self-adaptive, dynamic parameter adjustment algorithm is also utilized for the purpose of broad search and fast convergence. The optimization results shows that the performance and effectiveness of the proposed system is superior with respect to a reference hybrid system in which the active and passive systems are independently optimized.

An Efficient Search Algorithm for Flexible Manufacturing Systems (FMS) Scheduling Problem with Finite Capacity (유한용량 Flexible Manufacturing Systems(FMS) 스케줄링 문제에 대한 효율적인 탐색 알고리즘 연구)

  • Kim, Hwang-Ho;Choi, Jin-Young
    • IE interfaces
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    • v.22 no.1
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    • pp.10-16
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    • 2009
  • In this paper, we propose an efficient search algorithm for finding an optimal schedule to minimize makespan, while avoiding deadlock situation in Flexible Manufacturing Systems (FMS) with finite capacity, in which each job needs to be processed in several job stages for completion. The proposed algorithm uses a modeling and control method based on Petri-net. Especially, we improve the efficiency of the search algorithm by using a priority rule and an efficient bounding function during the search procedure. The performance of the proposed algorithm is evaluated through a numerical experiment, showing that it holds considerable promise for providing an optimal solution efficiently comparing to past work.

A Cross-Diamond-Triangle Search Algorithm for Fast Block-Matching Motion Estimation (고속 블록 정합 움직임 측정을 위한 십자-다이아몬드-삼각 탐색 알고리즘)

  • Kim, Seong-Hoon;Shin, Jae-Min;Oh, Seoung-Jun;Ahn, Chang-Beom;Park, Ho-Chong;Sim, Dong-Gyu
    • Journal of Broadcast Engineering
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    • v.10 no.3
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    • pp.357-371
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    • 2005
  • In this Paper, we propose a new motion search algorithm called CDTS (Cross-Diamond-Triangle Search algorithm) that uses optimal search pattern according to the position of a search area to improve the performance of CDS(Cross-Diamond Search algorithm) as well as CDHSs(Cross-Diamond-Hexagonal Searches algorithms). We analyze motion distributions in various test video sequences to apply optimal search pattern according to a position of search area. Based on the result of this analysis, we propose a new triangle-shaped search pattern whose structure is asymmetric while previous search patterns are generally symmetric in conventional algorithms. In CDTS, we apply cross- and diamond-shaped search patterns to central search areas, and triangle- and diamond-shaped patterns to the other areas. Applying CDTS to test video sequences, the proposed scheme can reduce search points more than CDS and CDHSs by 16.22$\%$ and 3.09$\%$, respectively, without any visual quality degradation.

Fuzzy genetic algorithm for optimal control (최적 제어에 대한 퍼지 유전 알고리즘의 적용 연구)

  • 박정식;이태용
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.297-300
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    • 1997
  • This paper uses genetic algorithm (GA) for optimal control. GA can find optimal control profile, but the profile may be oscillating feature. To make profile smooth, fuzzy genetic algorithm (FGA) is proposed. GA with fuzzy logic techniques for optimal control can make optimal control profile smooth. We describe the Fuzzy Genetic Algorithm that uses a fuzzy knowledge based system to control GA search. Result from the simulation example shows that GA can find optimal control profile and FGA makes a performance improvement over a simple GA.

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An Iterative Insertion Algorithm and a Hybrid Meta Heuristic for the Traveling Salesman Problem with Time Windows (시간제약이 있는 외판원 문제를 위한 메타휴리스틱 기법)

  • Kim, Byung-In
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.1
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    • pp.86-98
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    • 2007
  • This paper presents a heuristic algorithm for the traveling salesman problem with time windows (TSPTW). Aniterative insertion algorithm as a constructive search heuristic and a hybrid meta heuristic combining simulatedannealing and tabu search with the randomized selection of 2-interchange and a simple move operator as animproving search heuristic are proposed, Computational tests performed on 400 benchmark problem instancesshow that the proposed algorithm generates optimal or near-optimal solutions in most cases. New best knownheuristic values for many benchmark problem sets were obtained using the proposed approach.

An Application of Harmony Search Algorithm for Operational Cost Minimization of MicroGrid System (마이크로 그리드 운영비용 최소화를 위한 Harmony Search 알고리즘 응용)

  • Rhee, Sang-Bong;Kim, Kyu-Ho;Kim, Chul-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.7
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    • pp.1287-1293
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    • 2009
  • This paper presents an application of Harmony Search (HM) meta-heuristic optimization algorithm for optimal operation of microgrid system. The microgrid system considered in this paper consists of a wind turbine, a diesel generator, and a fuel cell. An one day load profile which divided 20 minute data and wind resource for wind turbine generator were used for the study. In optimization, the HS algorithm is used for solving the problem of microgrid system operation which a various generation resources are available to meet the customer load demand with minimum operating cost. The application of HS algorithm to optimal operation of microgrid proves its effectiveness to determine optimally the generating resources without any differences of load mismatch and having its nature of fast convergency time as compared to other optimization method.

Search Algorithm for Efficient Optimal Path based on Time-weighted (시간 가중치 기반 효율적인 최적 경로 탐색 기법 연구)

  • Her, Yu-sung;Kim, Tae-woo;Ahn, Yonghak
    • Journal of the Korea Convergence Society
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    • v.11 no.2
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    • pp.1-8
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    • 2020
  • In this paper, we propose an optimal path search algorithm between each node and midpoint that applies the time weighting. Services for using a location of mid point usually provide a mid point location-based on the location of users. There is a problem that is not efficient in terms of time because a location-based search method is only considered for location. To solve the problem of the existing location-based search method, the proposed algorithm sets the weights between each node and midpoint by reflecting user's location information and required time. Then, by utilizing that, it is possible to search for an optimum path. In addition, to increase the efficiency of the search, it ensures high accuracy by setting weights adaptively to the information given. Experimental results show that the proposed algorithm is able to find the optimal path to the midpoint compared with the existing method.