• Title/Summary/Keyword: Micro Genetic Algorithm

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Structural Health Monitoring of Harbor Caisson-type Structures using Harmony Search Method (최적화 화음탐색법을 이용한 항만 케이슨 구조물의 구조건전성 평가)

  • Lee, So-Young;Kim, Jeong-Tae;Yi, Jin-Hak;Kang, Yoon-Koo
    • Journal of Ocean Engineering and Technology
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    • v.23 no.1
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    • pp.122-128
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    • 2009
  • In this study, damage detection method using harmony search method and frequency response is proposed. In order to verify this method, the following approaches are implemented. Firstly, damage detection method using harmony search was developed. To detect damage, objective functions that minimize difference with natural frequency and modal strain energy from undamaged and damaged model are used. Secondly, efficiency of developed damage detection method was verified by damage detection of beam structure. And results of harmony search and micro genetic algorithm are compared and evaluated. Thirdly, numerical model was implemented for harbor caisson structure and damage scenario was determined. Lastly, damage detection was performed by proposed method and utility of proposed method is verified.

Optimal strengthening in RC Hollow Slab Bridges using ${\mu}$-GA (${\mu}$-GA에 의한 RC 중공슬래브교의 최적보강)

  • Choi, Se-Hyu;Park, Kyung-Sik
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.14 no.4
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    • pp.169-178
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    • 2010
  • In this study, the optimal strengthening by micro genetic algorithm(${\mu}$-GA) method is proposed for improvement of load-carrying capacity of RC hollow slab bridges using external prestressing. The Qeen-post type and King-post type are considered for the optimal strengthening. The type for optimal strengthening, deviator, areas of tendons and the number of anchor are calculated by ${\mu}$-GA. The objective function is constituted with dimensionless cost of tendon and steel for optimal strengthening. The constraints are formulated by design specification for bridges and anchors. The validity of this study is presented by analysis of the results after the optimal strengthening of the RC hollow slab bridge.

Discrete Optimum Design of Semi-rigid Steel Frames Using Refined Plastic Hinge Analysis and Genetic Algorithm (개선소성힌지해석과 유전자 알고리즘을 이용한 반강접 강골조의 이산최적설계)

  • Lee, Mal Suk;Yun, Young Mook;Kang, Moon Myoung
    • Journal of Korean Society of Steel Construction
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    • v.16 no.2 s.69
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    • pp.201-213
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    • 2004
  • A GA-based optimum design algorithm and a program for plane steel frame structures with semi-rigid connections are presented. The algorithm is incorporated with the refined plastic hinge analysis method wherein geometric nonlinearity is considered by using the stability functions of beam-column members, and material nonlinearity, by using the gradual stiffness degradation model that includes the effects of residual stresses, moment redistribution through the occurrence of plastic hinges, semi-rigid connections, and geometric imperfection of members. In the genetic algorithm, the tournament selection method and micro-GAs are employed. The fitness function for the genetic algorithm is expressed as an unconstrained function composed of objective and penalty functions. The objective and penalty functions are expressed as the weight of steel frames and the constraint functions, respectively. In particular, the constraint functions fulfill the requirements of load-carrying capacity, serviceability, ductility, and construction workability. To verify the appropriateness of the present method, the optimal design results of two plane steel frames with rigid and semi-rigid connections are compared.

Hierarchical Cellular Network Design with Channel Allocation Using Genetic Algorithm (유전자 알고리즘을 이용한 다중계층 채널할당 셀룰러 네트워크 설계)

  • Lee, Sang-Heon;Park, Hyun-Soo
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.10a
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    • pp.321-333
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    • 2005
  • With the limited frequency spectrum and an increasing demand for cellular communication services, the problem of channel assignment becomes increasingly important. However, finding a conflict free channel assignment with the minimum channel span is NP hard. As demand for services has expanded in the cellular segment, sever innovations have been made in order to increase the utilization of bandwidth. The innovations are cellular concept, dynamic channel assignment and hierarchical network design. Hierarchical network design holds the public eye because of increasing demand and quality of service to mobile users. We consider the frequency assignment problem and the base station placement simultaneously. Our model takes the candidate locations emanating from this process and the cost of assigning a frequency, operating and maintaining equipment as an input. In addition, we know the avenue and demand as an assumption. We propose the network about the profit maximization. This study can apply to GSM(Global System for Mobile Communication) which has 70% portion in the world. Hierarchical network design using GA(Genetic Algorithm) is the first three-tier (Macro, Micro, Pico) model, We increase the reality through applying to EMC (Electromagnetic Compatibility Constraints). Computational experiments on 72 problem instances which have 15${\sim}$40 candidate locations demonstrate the computational viability of our procedure. The result of experiments increases the reality and covers more than 90% of the demand.

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Optimum Design of High-Speed, Short Journal Bearings by Artificial Life Algorithm (인공생명 알고리듬에 의한 고속, 소폭 저널베어링의 최적설계)

  • Lee, Yun-Hi;Yang, Bo-Suk
    • 유체기계공업학회:학술대회논문집
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    • 1999.12a
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    • pp.324-332
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    • 1999
  • This paper presents the artificial life algorithm which is remarkable in the area of engineering for optimum design. As artificial life organisms have a sensing system, they can find the resource which they want to find and metabolize it. And the characteristics of artificial life are emergence and dynamical interacting with environment. In other words, the micro interaction with each other in the artificial life's group results in emergent colonization in the whole system. In this paper, therefore, artificial life algorithm by using above characteristics is employed into functions optimization. The effectiveness of this proposed algorithm is verified through the numerical test of single and multi objective functions. The numerical tests also show that the proposed algorithm is superior to genetic algorithm and immune algorithm for the Multi-peak function. And artificial life algorithm is also applied to optimum design of high-speed, short journal bearings and verified through the numerical test.

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Size and Shape Optimization of Truss Structures using Micro Genetic Algorithm (마이크로 유전 알고리즘을 이용한 트러스 구조물의 단면 및 형상 최적화)

  • Kim, Dae-Hwan;Yoon, Byoung-Wook;Lee, Jae-Hong
    • Journal of Korean Society of Steel Construction
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    • v.23 no.4
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    • pp.465-474
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    • 2011
  • In this study, a microgenetic algorithm was used to find the optimum cross-section and shape of dome structures. The allowable stress and Euler buckling stress were considered constraints when the weight of the trusses was minimum. The design optimization of the truss structures involved arriving at the optimum sizes of the cross-section and geometric coordinate. The features of the proposed method, which helped in the modeling of and application to the optimal design of truss structures, were demonstrated using the microgenetic algorithm, by solving sample problems.

Micro Channel Fabrication Technology Using UV Laser Micromachining (UV 레이저 마이크로머시닝을 이용한 마이크로 채널 제작기술)

  • 양성빈;장원석;김재구;신보성;전병희
    • Transactions of Materials Processing
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    • v.13 no.3
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    • pp.216-224
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    • 2004
  • In this study, we have developed a new UV$({\lambda}=355nm)$ laser micromachining technology by direct ablation method without masks. This technology allows that 3D micro parts can be fabricated rapidly and efficiently with a low price. And it has a benefit of reducing fabricating process simply. Due to micro parts' fabrication, such technologies need the control of XYZ stages with high precision, the design of optical devices to maintain micron spot sizes of laser beam and the control technology of laser focus. The developed laser manufacturing process for laser micromachining is that, after extracting coordinates of shape data from CAD model data, a beam path considering manufacturing features of laser beam is created by using genetic algorithm. This generated manufacturing process is sent to stage controller. In order to improve the surface quality of micro parts, we have carried out experiments on iteration manufacturing and beam step-over by using a minimum focus size. Moreover, we have fabricated a micro-channel through the developed laser micromachining technology and verified it through the results.

Knowledge based Genetic Algorithm for the Prediction of Peptides binding to HLA alleles common in Koreans (지식기반 유전자알고리즘을 이용한 한국인 빈발 HLA 대립유전자에 대한 결합 펩타이드 예측)

  • Cho, Yeon-Jin;Oh, Heung-Bum;Kim, Hyeon-Cheol
    • Journal of Internet Computing and Services
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    • v.13 no.4
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    • pp.45-52
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    • 2012
  • T cells induce immune responses and thereby eliminate infected micro-organisms when peptides from the microbial proteins are bound to HLAs in the host cell surfaces, It is known that the more stable the binding of peptide to HLA is, the stronger the T cell response gets to remove more effectively the source of infection. Accordingly, if peptides (HLA binder) which can be bound stably to a certain HLA are found, those peptieds are utilized to the development of peptide vaccine to prevent infectious diseases or even to cancer. However, HLA is highly polymorphic so that HLA has a large number of alleles with some frequencies even in one population. Therefore, it is very inefficient to find the peptides stably bound to a number of HLAs by testing random possible peptides for all the various alleles frequent in the population. In order to solve this problem, computational methods have recently been developed to predict peptides which are stably bound to a certain HLA. These methods could markedly decrease the number of candidate peptides to be examined by biological experiments. Accordingly, this paper not only introduces a method of machine learning to predict peptides binding to an HLA, but also suggests a new prediction model so called 'knowledge-based genetic algorithm' that has never been tried for HLA binding peptide prediction. Although based on genetic algorithm (GA). it showed more enhanced performance than GA by incorporating expert knowledge in the process of the algorithm. Furthermore, it could extract rules predicting the binding peptide of the HLA alleles common in Koreans.

Development and Efficiency Evaluation of Metropolis GA for the Structural Optimization (구조 최적화를 위한 Metropolis 유전자 알고리즘을 개발과 호율성 평가)

  • Park Kyun-Bin;Kim Jeong-Tae;Na Won-Bae;Ryu Yeon-Sun
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.19 no.1 s.71
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    • pp.27-37
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    • 2006
  • A Metropolis genetic algorithm (MGA) is developed and applied for the structural design optimization. In MGA, favorable features of Metropolis criterion of simulated annealing (SA) are incorporated in the reproduction operations of simple genetic algorithm (SGA). This way, the MGA maintains the wide varieties of individuals and preserves the potential genetic information of early generations. Consequently, the proposed MGA alleviates the disadvantages of premature convergence to a local optimum in SGA and time consuming computation for the precise global optimum in SA. Performances and applicability of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro GA, and Kirkpatrick's SA. Typical numerical examples are used to evaluate the computational performances, the favorable features and applicability of MGA. The effects of population sizes and maximum generations are also evaluated for the performance reliability and robustness of MGA. From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA Is a reliable and efficient tool for structural design optimization.

The optimum damper retrofit of cabinet structures by genetic (유전자알고리즘을 이용한 캐비닛 구조의 최적감쇠보강)

  • 이계희;최익창;하동호
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2004.10a
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    • pp.379-386
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    • 2004
  • The optimal seismic retrofitting of NPP(Nuclear Power Plant) cabinet structures that contained class 1 relays were studies in this paper. During earthquake event, the failure modes of relays are not appeared in form of structural failure, but are appeared in form of contact chatter of relay. Therefore, the retrofitting of cabinet has to be aimed to the reducing of the structural response, such as acceleration. In this study, the optimal characteristic values of dampers were searched by μ-GA (micro-Genetic Algorithm) scheme for several installation patterns. To keep accuracy and efficiency of analysis, the structural models of cabinet were considered as a frame structure. The responses of structure were obtained in form of acceleration response spectra derived from the results of nonlinear time history analysis including damping nonlinearity. The fitness function of the optimum procedure was constructed based on the ratio of maximum spectral value and target GERS (General Equipment Ruggedness Spectra). The results show the good improvements of fitness fur adequate retrofitting pattern. Especially, the improvements of fitness were remarkable when the damping exponents are proper.

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