• 제목/요약/키워드: Search algorithms

검색결과 1,328건 처리시간 0.024초

제약만족 최적화 문제를 위한 백트래킹 탐색의 구조화 (A Backtracking Search Framework for Constraint Satisfaction Optimization Problems)

  • 손석원
    • 정보처리학회논문지A
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    • 제18A권3호
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    • pp.115-122
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    • 2011
  • 모든 제약만족 최적화 문제의 해를 구하는 일반화된 알고리즘을 구하는 것은 매우 어렵다. 그러나 결정 변수의 특성에 따라 세분화된 문제는 해를 위한 알고리즘을 구하기에 더 쉽다는 가정을 할 수 있다. 이와 같은 가정 하에 문제를 세분화 시키는 문제분류규칙을 제안하고 세분화된 문제의 특성에 맞는 백트래킹 알고리즘을 개발한다. 백트래킹을 이용한 깊이우선탐색에서 해를 빨리 찾기 위한 방법 중 하나는 탐색되는 노드의 순서를 효과적으로 배열하는 것이다. 정적 특성이 우세한 무선 센서 네트워크의 클러스터 헤드 위치문제와 동적 및 정적 특성의 혼합특성을 갖는 RFID 리더 간섭 최소화 문제를 선택하여 최적의 변수 순서화 알고리즘을 개발하고 기존의 방법과 비교하였다. 결과적으로 문제를 세분화시킴으로써 체계적인 탐색을 위한 백트래킹의 구조화를 실현하였다. 또한 개발된 백트래킹 알고리즘의 성능이 우수함을 보였다.

전역 탐색 알고리즘을 이용한 유무선망의 최적화 (Optimization of wire and wireless network using Global Search Algorithm)

  • 오정근;변건식
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2002년도 추계종합학술대회
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    • pp.251-254
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    • 2002
  • 이동 무선 통신 시스템을 설계할 때 기지국(BTS), 기지국 콘트롤러(BSC), 이동 교환국(MSC)의 위치는 매우 중요한 파라미터 중 하나이다. 무선 통신 시스템을 설계할 때 여러 가지 복잡한 변수들을 잘 조합하여 비용이 최소가 되도록 설계해야 한다. 이러한 문제를 해결하는데 필요한 알고리즘이 전역 최적화 알고리즘이며, 지금까지 전역 최적화 검색 기술로 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm과 같은 조합 최적화 기술이 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 보여 준다.

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공생진화 알고리듬에서의 공생파트너 선택전략 분석 (Analysis of Partnering Strategies in Symbiotic Evolutionary Algorithms)

  • 김재윤;김여근;신태호
    • 한국경영과학회지
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    • 제25권4호
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    • pp.67-80
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    • 2000
  • Symbiotic evolutionary algorithms, also called cooperative coevolutionary algorithms, are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual required first selecting symbiotic partners of the individual. Several partner selection strategies are provided. The goal of this study is to analyze how much partnering strategies can influence the performance of the algorithms. With two types of test-bed problems: the NKC model and the binary string covering problem, extensive experiments are carried out to compare the performance of partnering strategies, using the analysis of variance. The experimental results indicate that there does not exist statistically significant difference in their performance.

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유전자 알고리즘을 이용한 2차원 강구조물의 최적설계 (Optimum Design of Two-Dimensional Steel Structures Using Genetic Algorithms)

  • 김봉익;권중현
    • 한국해양공학회지
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    • 제21권2호
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    • pp.75-80
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    • 2007
  • The design variables for structural systems, in most practical designs, are chosen from a list of discrete values, which are commercially available sizing. This paper presents the application of Genetic Algorithms for determining the optimum design for two-dimensional structures with discrete and pseudocontinuous design variables. Genetic Algorithms are heuristic search algorithms and are effective tools for finding global solutions for discrete optimization. In this paper, Genetic Algorithms are used as the method of Elitism and penalty parameters, in order to improve fitness in the reproduction process. Examples in this paper include: 10 bar planar truss and 1 bay 8-story frame. Truss with discrete and pseudoucontinuous design variables and steel frame with W-sections are used for the design of discrete optimization.

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

  • 전영현;윤종호;조화현;최명렬
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2005년도 추계종합학술대회
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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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병렬 기계 스케줄링을 위한 제한적 이웃해 생성 방안 (A Restricted Neighborhood Generation Scheme for Parallel Machine Scheduling)

  • 신현준;김성식
    • 산업공학
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    • 제15권4호
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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.

탐색 영역 재설정을 이용한 고속 움직임 예측 방법 (Fast Block Motion Estimation based on reduced search ranges in MPEG-4)

  • 김성제;서동완;최윤식
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.529-531
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    • 2005
  • A block-based fast motion estimation algorithm is proposed in this paper to perform motion estimation based on the efficiently reduced search ranges in MPEG-4(ERS). This algorithm divides the search areas into several small search areas and the candidate small search area that has the lowest average of sum norm difference between current macroblock and candidate macroblock is chosen to perform block motion estimation using the Nobel Successive Elimination Algorithm (NSEA). Experimental results of the proposed algorithm show that the averaging PSNR improvement is better maximum 0.125 dB than other tested algorithms and bit saving effect is maximum 20kbps for some tested sequences in low-bit rate circumstance.

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Optimum design of geometrically non-linear steel frames with semi-rigid connections using a harmony search algorithm

  • Degertekin, S.O.;Hayalioglu, M.S.;Gorgun, H.
    • Steel and Composite Structures
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    • 제9권6호
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    • pp.535-555
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    • 2009
  • The harmony search method based optimum design algorithm is presented for geometrically non-linear semi-rigid steel frames. Harmony search method is recently developed metaheuristic algorithm which simulates the process of producing a musical performance. The optimum design algorithm aims at obtaining minimum weight steel frames by selecting from standard set of steel sections such as European wide flange beams (HE sections). Strength constraints of Turkish Building Code for Steel Structures (TS648) specification and displacement constraints were used in the optimum design formulation. The optimum design algorithm takes into account both the geometric non-linearity of the frame members and the semi-rigid behaviour of the beam-to-column connections. The Frye-Morris polynomial model is used to calculate the moment-rotation relation of beam-to-column connections. The robustness of harmony search algorithm, in comparison with genetic algorithms, is verified with two benchmark examples. The comparisons revealed that the harmony search algorithm yielded not only minimum weight steel frames but also required less computational effort for the presented examples.

차량경로 문제에 대한 Guided Tabu 검색 (Study on the Guided Tabu Search for the Vehicle Routing Problem)

  • 이승우;이화기
    • 대한안전경영과학회지
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    • 제10권1호
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    • pp.145-153
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    • 2008
  • The vehicle routing problem determines each vehicle routes to find the transportation costs, subject to meeting the customer demands of all delivery points in geography. Vehicle routing problem is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a heuristic method which combines guided local search with a tabu search in order to minimize the transportation costs for the vehicle routing assignment and uses ILOG programming library to solve. The computational tests were performed using the benchmark problems. And computational experiments on these instances show that the proposed heuristic yields better results than the simple tabu search does.