• Title/Summary/Keyword: search algorithm

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A initial cluster center selection in FCM algorithm using the Genetic Algorithms (유전 알고리즘을 이용한 FCM 알고리즘의 초기 군집 중심 선택)

  • 오종상;정순원;박귀태
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.290-293
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    • 1996
  • This paper proposes a scheme of initial cluster center selection in FCM algorithm using the genetic algorithms. The FCM algorithm often fails in the search for global optimum because it is local search techniques that search for the optimum by using hill-climbing procedures. To solve this problem, we search for a hypersphere encircling each clusters whose parameters are estimated by the genetic algorithms. Then instead of a randomized initialization for fuzzy partition matrix in FCM algorithm, we initialize each cluster center by the center of a searched hypersphere. Our experimental results show that the proposed initializing scheme has higher probabilities of finding the global or near global optimal solutions than the traditional FCM algorithm.

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A Fast Motion Estimation Algorithm with Motion Analysis (움직임 해석을 통한 고속 움직임 예측 알고리즘)

  • Jun, Young-Hyun;Yun, Jong-Ho;Cho, Hwa-Hyun;Choi, Myung-Ryul
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.339-342
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    • 2005
  • We present an efficient block-based motion estimation algorithm with motion analysis. The motion analysis determines a size of search pattern and a maximum repeated count of search pattern. In case of large movement in large image, we reduce search points and the local minimum which caused by low performance. The proposed algorithm employs with searching step of 2. The first step determines an initial search point with neighbor block vector and a size of initial search pattern. The second step determines a size of search pattern and a maximum repeated count with motion analysis. We improve motion prediction accuracy while reducing required computational complexity compared to other fast block-based motion estimation algorithms.

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A Restricted Neighborhood Generation Scheme for Parallel Machine Scheduling (병렬 기계 스케줄링을 위한 제한적 이웃해 생성 방안)

  • Shin, Hyun-Joon;Kim, Sung-Shick
    • IE interfaces
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    • v.15 no.4
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    • pp.338-348
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    • 2002
  • In this paper, we present a restricted tabu search(RTS) algorithm that schedules jobs on identical parallel machines in order to minimize the maximum lateness of jobs. Jobs have release times and due dates. Also, sequence-dependent setup times exist between jobs. The RTS algorithm consists of two main parts. The first part is the MATCS(Modified Apparent Tardiness Cost with Setups) rule that provides an efficient initial schedule for the RTS. The second part is a search heuristic that employs a restricted neighborhood generation scheme with the elimination of non-efficient job moves in finding the best neighborhood schedule. The search heuristic reduces the tabu search effort greatly while obtaining the final schedules of good quality. The experimental results show that the proposed algorithm gives better solutions quickly than the existing heuristic algorithms such as the RHP(Rolling Horizon Procedure) heuristic, the basic tabu search, and simulated annealing.

A Neighborhood Beam Search Algorithm for Routing Yard-Side Equipment in Port Container Terminals (컨테이너 터미널에서 야드장비의 경로결정을 위한 이웃에 대한 빔 탐색 방식)

  • 김기영;김갑환
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 1998.10a
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    • pp.315-322
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    • 1998
  • It is discussed how to route yard-side equipment during the loading operation in port container terminals. The number of containers to be picked up at each yard-bay, as well as the route of a yard-side equipment (for example, transfer crane or straddle carrier) in a yard, are determined. The objective of the problem is to minimize the total container handling time in the yard. An encoding method to represent nodes in the search space is introduced utilizing inherent properties of the optimal solution by which the search space is greatly reduced. A beam search algorithm is suggested. A numerical experiment is carried out to compared the performance of the beam search algorithm with those of other approaches.

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A New Diversity Preserving Evolutionary Programming Technique (다양성을 유지하는 새로운 진화 프로그래밍 기법)

  • 신정환;진성일;최두현
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.1011-1014
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    • 1999
  • In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

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Parameter Calibration of the Nonlinear Muskingum Model using Harmony Search

  • Geem, Zong-Woo;Kim, Joong-Hoon;Yoon, Yong-Nam
    • Journal of Korea Water Resources Association
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    • v.33 no.S1
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    • pp.3-10
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    • 2000
  • A newly developed heuristic algorithm, Harmony Search, is applied to the parameter calibration problem of the nonlinear Muskingum model. The Harmony Search could, mimicking the improvisation of music player, find better parameter values for in the nonlinear Muskingum model than five other methods including another heuristic method, genetic algorithm, in the aspect of SSQ(the sum of the square of the deviations between the observed and routed outflows) as well as in the aspects of SAD(the sum of the absolute value of the deviations), DPO(deviations of peak of routed and actual flows) and DPOT(deviatios of peak time of routed and actual outflow). Harmony Search also has the advantage that it does not require the process of asuming the initial values of desing parameters. The sensitivity analysis of Harmony Memory Considering Rate showed that relatively large values of Harmony Memory Considering Rate makes the Harmony Search converge to a better solution.

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Application of Genetic Algorithm-Based Relay Search Method for Structure Design - Strengthening Problems (교대형 유전자 알고리즘을 이용한 보강설계의 최적화)

  • 정승인;김남희;장승필
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2001.04a
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    • pp.223-232
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    • 2001
  • This paper describes Genetic Algorithm-Based Relay Search Method, RS-GA, which is developed in this study to search the multiple design variables in the design space. The RS-GA based on Simple-GA consists of some functions to search many variables from some wide variable space. It repeats a Simple-GA, that is the convergence process of the Simple-GA, which makes many time reiteration itself. From the results of the numerical studies, it was actually found that RS-GA can search all peak-variable from the 2D functions including 5 peaks. Finally, RS-GA applied for design-strengthening problems in composite plate girder bridges using the external prestressing technique is also verified.

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Parameter Calibration o fthe Nonlinear Muskingum Model using Harmony Search

  • Geem, Jong-Woo;Kim, Joong-Hoon;Yoon, Yong-Nam
    • Proceedings of the Korea Water Resources Association Conference
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    • 2000.05a
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    • pp.3-10
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    • 2000
  • A newly developed heuristic algorithm, Harmony Search, is applied to the parameter calibration problem of the nonlinear Muskingum model. The Harmony Search could, mimicking the improvisation of music players, find better parameter values for in the nonlinear Muskingum model than five other methods including another heuristic method, genetic algorithm, in the aspect of SSQ (the sum of the square of the deviations between the observed and routed outflows) as well as in the aspects of SAD (the sum of the absolute value of the deviations), DPO (deviations of peak of routed and actual flows) and DPOT (deviations of peak time of rented and actual outflow). Harmony Search also has the advantage that it does not require the process of assuming the initial values of design parameters. The sensitivity analysis of Harmony Memory Considering Rate showed that relatively large values of Harmony Memory Considering Rate makes the Harmony Search converse to a better solution.

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A Fast Block Matching Motion Estimation Algorithm by using the Enhanced Cross-Hexagonal Search Pattern (개선된 크로스-육각 패턴을 이용한 고속 블록 정합 움직임 추정 알고리즘)

  • Nam Hyeon-Woo
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.4 s.42
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    • pp.77-85
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    • 2006
  • There is the spatial correlation of the video sequence between the motion vector of current blocks. In this paper, we propose the enhanced fast block matching algorithm using the spatial correlation of the video sequence and the center-biased properly of motion vectors. The proposed algorithm determines an exact motion vector using the predicted motion vector from the adjacent macro blocks of the current frame and the Cross-Hexagonal search pattern. From the of experimental results, we can see that our proposed algorithm outperforms both the prediction search algorithm (NNS) and the fast block matching algorithm (CHS) in terms of the search speed and the coded video's quality. Using our algorithm, we can improve the search speed by up to $0.1{\sim}38%$ and also diminish the PSNR (Peak Signal Noise Ratio) by at nst $0.05{\sim}2.5dB$, thereby improving the video qualify.

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Development of the Meta-heuristic Optimization Algorithm: Exponential Bandwidth Harmony Search with Centralized Global Search (새로운 메타 휴리스틱 최적화 알고리즘의 개발: Exponential Bandwidth Harmony Search with Centralized Global Search)

  • Kim, Young Nam;Lee, Eui Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.2
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    • pp.8-18
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    • 2020
  • An Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was developed to enhance the performance of a Harmony Search (HS). EBHS-CGS added two methods to improve the performance of HS. The first method is an improvement of bandwidth (bw) that enhances the local search. This method replaces the existing bw with an exponential bw and reduces the bw value as the iteration proceeds. This form of bw allows for an accurate local search, which enables the algorithm to obtain more accurate values. The second method is to reduce the search range for an efficient global search. This method reduces the search space by considering the best decision variable in Harmony Memory (HM). This process is carried out separately from the global search of the HS by the new parameter, Centralized Global Search Rate (CGSR). The reduced search space enables an effective global search, which improves the performance of the algorithm. The proposed algorithm was applied to a representative optimization problem (math and engineering), and the results of the application were compared with the HS and better Improved Harmony Search (IHS).