• Title/Summary/Keyword: GA 알고리듬

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A Comparative Study of Genetic Algorithm and Mathematical Programming Technique applied in Design Optimization of Geodesic Dome (지오데식 돔의 설계최적화에서 유전알고리즘과 수학적계획법의 비교연구)

  • Lee, Sang-Jin;Lee, Hyeon-Jin
    • Proceeding of KASS Symposium
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    • 2008.05a
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    • pp.101-106
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    • 2008
  • This paper describes a comparative study of genetic algorithm and mathematical programming technique applied in the design optimization of geodesic dome. In particular, the genetic algorithm adopted in this study uses the so-called re-birthing technique together with the standard GA operations such as fitness, selection, crossover and mutation to accelerate the searching process. The finite difference method is used to calculate the design sensitivity required in mathematical programming techniques and three different techniques such as sequential linear programming (SLP), sequential quadratic programming(SQP) and modified feasible direction method(MFDM) are consistently used in the design optimization of geodesic dome. The optimum member sizes of geodesic dome against several external loads is evaluated by the codes $ISADO-GA{\alpha}$ and ISADO-OPT. From a numerical example, we found that both optimization techniques such as GA and mathematical programming technique are very effective to calculate the optimum member sizes of three dimensional discrete structures and it can provide a very useful information on the existing structural system and it also has a great potential to produce new structural system for large spatial structures.

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Real-Time Multiple-Parameter Tuning of PPF Controllers for Smart Structures by Genetic Algorithms (유전자 알고리듬을 이용한 지능구조물의 PPF 제어기 실시간 다중변수 조정)

  • Heo, Seok;Kwak, Moon-Kyu
    • Journal of KSNVE
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    • v.11 no.1
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    • pp.147-155
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    • 2001
  • This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

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Modified AntNet Algorithm for Network Routing (네트워크 라우팅을 위한 개선된 AntNet 알고리즘)

  • Kang, Duk-Hee;Lee, Mal-Rey
    • Journal of KIISE:Software and Applications
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    • v.36 no.5
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    • pp.396-400
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    • 2009
  • During periods of large data transmission, routing selection methods are used to efficiently manage data traffic and improve the speed of transmission. One approach in routing selection is AntNet that applies the Ant algorithm in transmissions with uniform probability. However, this approach uses random selection, which can cause excessive data transmission rates and fail to optimize data This paper presents the use of the Genetic Algorithm (GA) to efficiently route and disperse data transmissions, during periods with "unnecessary weight increases for random selection". This new algorithm for improved performance provides highly accurate estimates of the transmission time and the transmission error rate.

Construction of Database on Turbulent Properties of a Circular Cylinder with a 3D-PTV Technique (3차원 PTV에 의한 원주후류 난류통계량 데이터베이스 구축)

  • Doh D. H.;Cho Y B.;;Pyeon Y. B.;Baek T. S.
    • Proceedings of the KSME Conference
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    • 2002.08a
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    • pp.249-252
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    • 2002
  • Turbulent properties of the wake of a circular cylinder were measured The diameter of the cylinder is l0mm and the Reynolds number is 420. A new 3D-PTY system was constructed and a genetic algorithm (GA) was introduced in order to increase the number of instantaneous three-dimensional velocity vectors. In the GA two fitness functions were introduced in order to enhance the correspondences of the particles. The measurement system consists of three CCD cameras, Ar-ion laser, an image grabber and a host computer. More than 3000 instantaneous three-dimensional velocity vectors were obtained by the system. The database of the turbulent properties of the circular cylinder was constructed by the constructed 3D-PTV system.

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Global Optimization Using Differential Evolution Algorithm (차분진화 알고리듬을 이용한 전역최적화)

  • Jung, Jae-Joon;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.11
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    • pp.1809-1814
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    • 2003
  • Differential evolution (DE) algorithm is presented and applied to global optimization in this research. DE suggested initially fur the solution to Chebychev polynomial fitting problem is similar to genetic algorithm(GA) including crossover, mutation and selection process. However, differential evolution algorithm is simpler than GA because it uses a vector concept in populating process. And DE turns out to be converged faster than CA, since it employs the difference information as pseudo-sensitivity In this paper, a trial vector and its control parameters of DE are examined and unconstrained optimization problems of highly nonlinear multimodal functions are demonstrated. To illustrate the efficiency of DE, convergence rates and robustness of global optimization algorithms are compared with those of simple GA.

Convergence Enhanced Successive Zooming Genetic Algorithm far Continuous Optimization Problems (연속 최적화 문제에 대한 수렴성이 개선된 순차적 주밍 유전자 알고리듬)

  • Gwon, Yeong-Du;Gwon, Sun-Beom;Gu, Nam-Seo;Jin, Seung-Bo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.2
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    • pp.406-414
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    • 2002
  • A new approach, referred to as a successive zooming genetic algorithm (SZGA), is Proposed for identifying a global solution for continuous optimization problems. In order to improve the local fine-tuning capability of GA, we introduced a new method whereby the search space is zoomed around the design point with the best fitness per 100 generation. Furthermore, the reliability of the optimized solution is determined based on the theory of probability. To demonstrate the superiority of the proposed algorithm, a simple genetic algorithm, micro genetic algorithm, and the proposed algorithm were tested as regards for the minimization of a multiminima function as well as simple functions. The results confirmed that the proposed SZGA significantly improved the ability of the algorithm to identify a precise global minimum. As an example of structural optimization, the SZGA was applied to the optimal location of support points for weight minimization in the radial gate of a dam structure. The proposed algorithm identified a more exact optimum value than the standard genetic algorithms.

Genetic Algorithm Based Optimal Design for an Automobile Mirror Actuator (유전자 알고리듬을 이용한 자동차용 Mirror Actuator의 최적설계)

  • Park, Won-Ho;Kim, Chae-Sil;Choi, Heon-Oh
    • Proceedings of the KSME Conference
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    • 2001.06c
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    • pp.559-564
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    • 2001
  • The design of an automobile mirror actuator system needs a systematic optimization due to several variables, constraints, geometric limitations, moving angle, and so on. Therefore, this article provides the procedure of a genetic algorithm(GA) based optimization with finite element analysis for design of a mirror actuator considering design constraints, geometric limitations, moving angle. Local optimum problem in optimization design with sensitivity analysis is overcome by using zero-order overall searching method which is new optimization design method using a genetic algorithm.

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A Study on the design Optimization of Thickness of Machiningcenter Bed under Dynamic Loading by using Genetic Algorithm (유전적 알고리듬을 적용하여 머시닝센터 베드두께의 동하중을 고려한 최적설계에 관한 연구)

  • 조백희
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.8 no.1
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    • pp.67-73
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    • 1999
  • This paper presents resizing design optimization method by utilizing genetic algorithm(GA), which consists of three basic operators : reproduction, crossover and mutation. The fitness and penalty function for resizing optimization problem are defined, and the flowchart of the developed computer program along with the descriptions of each modules is presented. Also, modelling for flexible-body dynamic analysis is presented. The model is composed of bodies, joints, and force elements such as translational spring-damper-actuator. The design objects si to determine the wall thickness for minimum weight under dynamic displacement constraint.

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Optimization of a Membrane with a Center Hole using Natural Element Method and Genetic Algorithm (자연요소법과 유전자 알고리듬을 사용한 원공 평판의 최적설계)

  • Lee, Sang-Bum;Seong, Hwal-Gyeng;Cheon, Ho-Jeong
    • Journal of the Korean Society for Precision Engineering
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    • v.25 no.2
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    • pp.105-114
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    • 2008
  • Natural element method (NEM) is quick in research activities by natural sciences and mechanical engineering fields, and from which good results are watched by various engineering fields and applied too. However no paper or research about the applied case has announced yet. Therefore on this paper, I will rediscover an optimum design and apply NEM into other fields with NEM for existing optimum design of mainly using FEM. NEM and genetic algorithm (GA) are applied to optimize a membrane with a center hole. The optimal design obtained by NEM is compared to the counterpart obtained by the finite element method (FEM). Result by NEM is found to be better than the result by FEM. NEM can be a feasible analysis tool in design optimization.

Electrode Shape Optimization of Piezo Sensors Using Genetic Algorithm (유전 알고리듬을 이용한 압전센서의 전극형상 최적화)

  • Lee Ki-Moon;Park Hyun-Chul;Park Chul-Hue
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.6 s.249
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    • pp.698-704
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    • 2006
  • This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.