• Title/Summary/Keyword: 변형 유전 알고리즘

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An Analytical Study on System Identification of Steel Beam Structure for Buildings based on Modified Genetic Algorithm (변형 유전 알고리즘을 이용한 건물 철골 보 구조물의 시스템 식별에 관한 해석적 연구)

  • Oh, Byung-Kwan;Choi, Se-Woon;Kim, Yousok;Cho, Tong-Jun;Park, Hyo-Seon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.27 no.4
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    • pp.231-238
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    • 2014
  • In the buildings, the systems of structures are influenced by the gravity load changes due to room alteration or construction stage. This paper proposes a system identification method establishing mass as well as stiffness to parameters in model updating process considering mass change in the buildings. In this proposed method, modified genetic algorithm, which is optimization technique, is applied to search those parameters while minimizing the difference of dynamic characteristics between measurement and FE model. To search more global solution, the proposed modified genetic algorithm searches in the wider search space. It is verified that the proposed method identifies the system of structure appropriately through the analytical study on a steel beam structure in the building. The comparison for performance of modified genetic algorithm and existing simple genetic algorithm is carried out. Furthermore, the existing model updating method neglecting mass change is performed to compare with the proposed method.

A Hybrid Genetic Algorithm Using Epistasis Information for Sequential Ordering Problems (서열순서화문제를 위한 상위정보를 이용하는 혼합형 유전 알고리즘)

  • Seo Dong-Il;Moon Byung-Ro
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.6
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    • pp.661-667
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    • 2005
  • In this paper, we propose a new hybrid genetic algorithm for sequential ordering problem (SOP). In the proposed genetic algorithm, the Voronoi quantized crossover (VQX) is used as a crossover operator and the path-preserving 3-Opt is used as a local search heuristic. VQX is a crossotver operator that uses the epistasis information of given problem instance. Since it is a crossover proposed originally for the traveling salesman problem (TSP), its application to SOP requires considerable modification. In this study, we appropriately modify VQX for SOP, and develop three algorithms, required in the modified VQX, named Feasible solution Generation Algorithm, Precedence Cycle Decomposition Algorithm, and Genic Distance Assignment Method. The results of the tests on SOP instances obtained from TSPLIB and ZIB-MP-Testdata show that the proposed genetic algorithm outperforms other genetic algorithms in stability and solution quality.

Damage Detection of Truss Structures Using Genetic Algorithm (유전 알고리즘을 이용한 트러스 구조물 손상탐지)

  • Kim, Hyung-Mi;Lee, Jae-Hong
    • Journal of Korean Society of Steel Construction
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    • v.24 no.5
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    • pp.549-558
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    • 2012
  • This study identifies the damage detection of truss structures by using genetic algorithm(GA) from changed elements properties. To model the damaged truss structures, the modulus of elasticity of some specific elements is reduced. The analysis of truss structures is performed with static analysis by applying uniform load, and the location and extent of structural damage is detected by comparing the stain of each element of healthy truss structures with damaged truss structures using genetic algorithm. In this study, some numerical examples are presented to detect the location and extent of damage using genetic algorithm.

A Genetic Algorithm with Modified Mutation for the Traveling Salesman Problem (외판원 문제를 위한 변형된 돌연변이를 적용한 유전 알고리즘)

  • 김정숙;홍영식
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.744-746
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    • 1998
  • 외판원(Traveling Salesman Problem)는 계산 복잡도가 매우 높으므로 이를 해결하려는 다양한 방법들이 제시되어 왔다. 최근에는 특히 휴리스틱(Heuristic) 에 기반한 유전 알고리즘(Genetic Algorithm)에 위한 방법이 관심을 집중시키고 있고, 이를 위한 다양한 교잡(Crossiver)연산자와 돌연변이(Mutation) 연산자들이 발표되고 있다. 돌연변이연산자는 지역해에 빠지는 것을 방지하며, 유용한 유전 특성을 잃어버릴 위험이 있는 교잡 연산자의 단점을 보완할 수 있다. 본 논문에서는 새로운 돌연변이 연산자를 개발하여 적용한 유전 알고리즘으로 외판원 문제를 해결한다.

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A Study on Metamorphosed-Genetic Algorithms by Applying the Meiosis for the Chromosome (염색체의 감수분열을 응용한 변형 유전알고리즘에 대한 연구)

  • Lee, Deog-Kyoo;Ko, Soung-Jun;Yi, Seok-Joo;Kim, You-Nam;Kim, Hag-Bae
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.6
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    • pp.1844-1851
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    • 2000
  • In this paper, a metamorphosed genetic algorithm based on the meiosis for human's chromosome is presented. In the algorithm, chromosomes in an individual are divided in half and in the other are divided into other rate. By our definition, they are composed of gametes with X-type chromosomes or Y-type chromosomes or especially M(mutation)-type chromosomes. When tow gametes among them are randomly selected and recombined, the new individual is correspondingly generated. Without reducing the searching space significantly, the global solution can be readily searched by new generated individual. The performance of he presented algorithm is examined and evaluated through proper simulation using test functions.

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Stereo Matching Using Genetic Algorithm and Region Information (유전 알고리즘과 영역 정보를 이용한 스테레오 정합)

  • 한규필;배태민;정의윤;김희수;하영호
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.3
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    • pp.97-105
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    • 1999
  • 본 논문에서는 기존의 깊이 복원 방법을 개선하기 위해서 유전 알고리즘을 이용한 새로운 스테레오 정합법을 제시하였고 다양한 영상에 적용하기 위해 영상의 영역 정보를 고려하였다. 유전 알고리즘은 자연선택과 개체군 유전학에 기반한 효율적인 탐색 기법인데, 이들의 염색체 교차와 돌연변이 같은 연산자를 정합 환경에 적합하도록 변형시켰다. 영상신호를 쉽게 다루기 위해서 2차원 염색체 구조를 사용하였으며, 스테레오 정합에 많이 사용되는 유사성과 연속성 제약 조건에 기반하여 적자를 선택하는 적응 함수를 정의하였다. 그리고 기존 유전 알고리즘의 수렴속도를 개선하기 위해서 무작위로 변이를 발생시키지 않고 휘도차를 이용하여 변이를 발생시키는 정보기반 변이 발생을 사용하였다. 실험을 통하여 본 방법은 이완처리를 포함한 정합법보다 계산 부하를 줄일 수 있었고 비교적 안정된 결과를 얻을 수 있었다.

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A Compact Stereo Matching Algorithm Using Modified Population-Based Incremental Learning (변형된 개체기반 증가 학습을 이용한 소형 스테레오 정합 알고리즘)

  • Han, Kyu-Phil;Chung, Eui-Yoon;Min, Gak;Kim, Gi-Seok;Ha, Yeong-Ho
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.10
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    • pp.103-112
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    • 1999
  • Genetic algorithm, which uses principles of natural selection and population genetics, is an efficient method to find out an optimal solution. In conventional genetic algorithms, however, the size of gene pool needs to be increased to insure a convergency. Therefore, many memory spaces and much computation time were needed. Also, since child chromosomes were generated by chromosome crossover and gene mutation, the algorithms have a complex structure. Thus, in this paper, a compact stereo matching algorithm using a population-based incremental learning based on probability vector is proposed to reduce these problems. The PBIL method is modified for matching environment. Since th proposed algorithm uses a probability vector and eliminates gene pool, chromosome crossover, and gene mutation, the matching algorithm is simple and the computation load is considerably reduced. Even though the characteristics of images are changed, stable outputs are obtained without the modification of the matching algorithm.

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Improved Genetic Algorithm-Based Damage Detection Technique Using Natural Frequency and Modal Strain Energy (고유진동수와 모드변형에너지를 이용한 향상된 유전알고리즘 기반 손상검색기법)

  • Park Jae-Hyung;Ryu Yeon-Sun;Yi Jin-Hak;Kim Jeong-Tae
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.19 no.3 s.73
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    • pp.313-322
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    • 2006
  • In the genetic algoricm (GA) based damage detection methods using vibration of structures, the selection of modal properties is important to improve the accuracy of damage detection. The objective of this study is to improve the accuracy of damage detection using natural frequency and modal strain energy, The following approaches are used to achieve the goal. First, modal strain energy is formulated and a new GA-based damage detection technique using natural frequency and modal strain energy is proposed. Next, to verify the efficiency of proposed technique, damage scenarios for free-free beam are designed and vibration modal tests of the target structure are conducted. Finally, the feasibility of the proposed technique is verified in comparison with other GA-based damage detection technique using natural frequency and mode shape.

Geoacoustic Parameters Inversion Using Parallel Multi-Population Genetic Algorithm (병렬 다중 개체군 유전 알고리즘을 이용한 지음향 파라미터 역산)

  • Oh Taekhwan;Na Jungyul;Lee Seongwook;Kim Seongil;Park Joung-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.6
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    • pp.309-316
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    • 2005
  • This paper Presents the geoacoustic inversion with Parallel Multi-Population Genetic Algorithm (PMPGA). This method is the modified form of simple genetic algorithm (SGA), which is devised for complementing the defects of simple genetic algorithm. The light bulb source and vertical line array (VLA) receiver are used for geoacoustic inversion. The results of this study show the geoacoustic Parameters can be estimated by PMPGA and the proposed algorithm is 1.7 times as fast as serial one on an average.

Shipyard Skid Sequence Optimization Using a Hybrid Genetic Algorithm

  • Min-Jae Choi;Yung-Keun Kwon
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.79-87
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    • 2023
  • In this paper, we propose a novel genetic algorithm to reduce the overall span time by optimizing the skid insertion sequence in the shipyard subassembly process. We represented a solution by a permutation of a set of skid ids and applied genetic operators suitable for such a representation. In addition, we combined the genetic algorithm and the existing heuristic algorithm called UniDev which is properly modified to improve the search performance. In particular, the slow skid search part in UniDev was changed to a greedy algorithm. Through extensive large-scaled simulations, it was observed that the span time of our method was stably minimized compared to Multi-Start search and a genetic algorithm combined with UniDev.