• 제목/요약/키워드: search algorithm

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A novel heuristic search algorithm for optimization with application to structural damage identification

  • Nobahari, Mehdi;Ghasemi, Mohammad Reza;Shabakhty, Naser
    • Smart Structures and Systems
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    • 제19권4호
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    • pp.449-461
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    • 2017
  • One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

혼합모델 양면조립라인의 밸런싱과 투입순서를 위한 내공생 진화알고리즘 (An Endosymbiotic Evolutionary Algorithm for Balancing and Sequencing in Mixed-Model Two-Sided Assembly Lines)

  • 조준영;김여근
    • 한국경영과학회지
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    • 제37권3호
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    • pp.39-55
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    • 2012
  • This paper presents an endosymbiotic evolutionary algorithm (EEA) to solve both problems of line balancing and model sequencing in a mixed-model two-sided assembly line (MMtAL) simultaneously. It is important to have a proper balancing and model sequencing for an efficient operation of MMtAL. EEA imitates the natural evolution process of endosymbionts, which is an extension of existing symbiotic evolutionary algorithms. It provides a proper balance between parallel search with the separated individuals representing partial solutions and integrated search with endosymbionts representing entire solutions. The strategy of localized coevolution and the concept of steady-state genetic algorithms are used to improve the search efficiency. The experimental results reveal that EEA is better than two compared symbiotic evolutionary algorithms as well as a traditional genetic algorithm in solution quality.

움직임 벡터 추정을 위한 탐색 영역 결정 방식 (A Search Range Decision Algorithm For Motion Vector Estimation)

  • 이민구;홍민철
    • 한국통신학회논문지
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    • 제28권2C호
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    • pp.141-146
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    • 2003
  • 본 논문은 동영상 압축 방식에서 사용되는 움직임 벡터 추정의 탐색 영역을 적응적으로 결정하는 방식에 대해 제안한다. 일반적인 동영상 압축 방식에서 사용되는 움직임 벡터 예측 방식의 성능은 압축 효율을 결정하는 움직임 벡터 예측을 위한 전처리 과정의 역할을 하는 제안된 동적 탐색 영역 방식은 인접 블록의 움직임 벡터의 통계적 특성에 따라 효율적으로 탐색 영역을 결정하여 영상 화질의 저하 없이 평균 60(%) 이상의 계산량을 절감하게 된다. 제안된 방식의 성능은 실험을 통해서 확인할 수 있었다.

2-레벨 탐색을 이용한 스피어 디코딩 알고리즘 (Sphere Decoding Algorithm Using Two-Level Search)

  • 현 트롱안;조종민;김진상;조원경
    • 한국통신학회논문지
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    • 제33권12A호
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    • pp.1133-1137
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    • 2008
  • 스피어 디코딩은 MIMO 심볼검출 기법 중 가장 유망한 기법 중 하나로 알려져 있다. 본 논문에서는 새로운 2 레벨 탐색 스피어 디코딩 알고리즘을 제안한다. 제안된 알고리즘은 심볼검출 시에 성능향상에 영향을 줄 수 있는 유용한 후보군이 이전 단계에서 버려지는 것을 피하기 위해서, 2 레벨 트리 탐색을 동시에 수행한다. 시뮬레이션 결과, 제안된 알고리즘이 BER 측면에서 기존의 알고리즘보다 성능이 우수함을 확인하였다.

적응형 윈도우 크기 기반 NTSS(New Three-Step Search Algorithm) 알고리즘 방법 (An Study Adaptive Winoow Size based NTSS Algorithm)

  • 유종훈;오승준;안창범
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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    • pp.451-453
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    • 2004
  • NTSS(New Three-Step Search Algorithm)는 대표적인 Fast BMA(Block Matching 시gorithm)인 TSS(Three-Step Search Algorithm)에 중앙 편향적(Center-Biased) 특성을 고려하여 향상시킨 방법이다. 그러나 NTSS는 움직임이 작은 영상인 경우에는 TSS보다 개선된 성능을 보여주지만, 움직임이 큰 영상에 대해서는 TSS와 큰 차이가 없으며 탐색영역이 커질수록 오히려 성능이 떨어지는 단점이 있다. 본 논문에서는 움직임 벡터의 특성에 맞는 탐색영역을 적용시킴으로써 탐색영역의 증가로 발생되는 NTSS의 단점을 보완하여 움직임이 큰 영상에 대해서도 향상된 성능을 갖는 방법을 제안한다. 제안된 방법을 적용 하였을때 움직임이 작은 영상에서는 기존의 방법과 동등한 결과를 얻었으며 움직임이 큰 영상에서는 최고 0.5db이상 성능이 개선되었다.

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Distributed Database Design using Evolutionary Algorithms

  • Tosun, Umut
    • Journal of Communications and Networks
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    • 제16권4호
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    • pp.430-435
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    • 2014
  • The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

베전 계통의 손실 최소화를 위한 시뮬레이티드 어닐링과 타부 탐색의 적용 (Application of Simulated Annealing and Tabu Search for Loss Minimization in Distribution Systems)

  • 전영재;김재철
    • 대한전기학회논문지:전력기술부문A
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    • 제50권1호
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    • pp.28-37
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    • 2001
  • This paper presents an efficient algorithm for the loss minimization of distribution system by automatic sectionalizing switch operation in large scale distribution systems. Simulated annealing is particularly well suited for large combinational optimization problem, but the use of this algorithm is also responsible for an excessive computation time requirement. Tabu search attempts to determine a better solution in the manner of a greatest-descent algorithm, but it can not give any guarantee for the convergence property. The hybrid algorithm of two methods with two tabu lists and the proposed perturbation mechanism is applied to improve the computation time and convergence property Numerical examples demonstrate the validity and effectiveness of the proposed methodology using a KEPCO's distribution system.

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Optimum design of multi-span composite box girder bridges using Cuckoo Search algorithm

  • Kaveh, A.;Bakhshpoori, T.;Barkhori, M.
    • Steel and Composite Structures
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    • 제17권5호
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    • pp.705-719
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    • 2014
  • Composite steel-concrete box girders are frequently used in bridge construction for their economic and structural advantages. An integrated metaheuristic based optimization procedure is proposed for discrete size optimization of straight multi-span steel box girders with the objective of minimizing the self-weight of girder. The metaheuristic algorithm of choice is the Cuckoo Search (CS) algorithm. The optimum design of a box girder is characterized by geometry, serviceability and ultimate limit states specified by the American Association of State Highway and Transportation Officials (AASHTO). Size optimization of a practical design example investigates the efficiency of this optimization approach and leads to around 15% of saving in material.

전역 탐색 알고리듬을 이용한 이동 무선통신 네트워크의 최적화에 대한 연구 (A Study on Mobile Wireless Communication Network Optimization Using Global Search Algorithm)

  • 김성곤
    • 한국컴퓨터정보학회논문지
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    • 제9권1호
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    • pp.87-93
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    • 2004
  • 이동 무선 통신 네트워크를 설계할 때 기지국(BTS), 기지국 콘트롤러(BSC), 이동 교환국(MSC)의 위치는 매우 중요한 파라미터들이다. 기지국의 위치를 설계할 때는 여러 가지 복잡한 변수들을 잘 조합하여 비용이 최소가 되도록 설계해야 한다 이러한 문제를 해결하는데 필요한 알고리듬이 전역 최적화 알고리듬이며, 지금까지 전역 최적화 검색 기술로는 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm이 사용되어 왔다. 본 논문은 이동 통신 시스템의 기지국, 기지국 콘트롤러, 이동 교환국의 위치 최적화에 위의 4가지 알고리듬들을 적용하여 각 알고리듬의 결과를 비교 분석하며 알고리듬에 의한 최적화 과정을 보여준다.

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An On-line Algorithm to Search Minimum Total Error for Imprecise Real-time Tasks with 0/1 Constraint

  • Song Gi-Hyeon
    • 한국멀티미디어학회논문지
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    • 제8권12호
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    • pp.1589-1596
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    • 2005
  • The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et al suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. On the other hand, in the case of on line scheduling, Shih and Liu proposed the NORA algorithm which can find a schedule with the minimum total error for a task system consisting solely of on-line tasks that are ready upon arrival. But, for the task system with 0/1 constraint, it has not been known whether the NORA algorithm can be optimal or not in the sense that it guarantees all mandatory tasks are completed by their deadlines and the total error is minimized. So, this paper suggests an optimal algorithm to search minimum total error for the imprecise on-line real-time task system with 0/1 constraint. Furthermore, the proposed algorithm has the same complexity, O(N log N), as the NORA algorithm, where N is the number of tasks.

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