• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 II
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• pp.805-809
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• 2001

This paper is presented to determine the optimal parameters of squeeze film damper using an enhanced genetic algorithm (EGA). The damper design parameters are the radius, length and radial clearance of the damper. The objective function is minimization of a transmitted load between bearing and foundation at the operating and critical speeds of a flexible rotor. The present algorithm was the synthesis of a genetic algorithm with simplex method for a local concentrate search. This hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution and can find both the global and local optimum solution. The numerical example is presented that illustrated the effectiveness of enhanced genetic algorithm for the optimal design of the squeeze film damper for reducing transmitted load.

• 한국전자파학회논문지
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• 제25권5호
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• pp.592-600
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• 2014

본 논문에서는 2차 함수 곡선의 회전체 곡면 위에 있는 배열 안테나의 빔 합성을 위한 Enhanced Adaptive Genetic Algorithm(EAGA)을 제안하였다. 제안된 알고리즘은 더 빠른 수렴 속도와 더 낮은 비용함수 값을 얻기 위해 Adaptive Genetic Algorithm(AGA)과 Invasive Weed Optimization(IWO)을 결합시켰다. 각 안테나 소자의 급전 크기와 위상의 최적화된 값은 EAGA를 통해 구하였으며, 이 결과를 통해 EAGA가 컨포멀 배열 안테나의 패턴 합성 알고리즘으로써 AGA보다 더 우수함을 보였다.

• Journal of Mechanical Science and Technology
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• 제17권12호
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• pp.1938-1948
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• 2003

This paper represents that an enhanced genetic algorithm (EGA) is applied to optimal design of a squeeze film damper (SFD) to minimize the maximum transmitted load between the bearing and foundation in the operational speed range. A general genetic algorithm (GA) is well known as a useful global optimization technique for complex and nonlinear optimization problems. The EGA consists of the GA to optimize multi-modal functions and the simplex method to search intensively the candidate solutions by the GA for optimal solutions. The performance of the EGA with a benchmark function is compared to them by the IGA (Immune-Genetic Algorithm) and SQP (Sequential Quadratic Programming). The radius, length and radial clearance of the SFD are defined as the design parameters. The objective function is the minimization of a maximum transmitted load of a flexible rotor system with the nonlinear SFDs in the operating speed range. The effectiveness of the EGA for the optimal design of the SFD is discussed from a numerical example.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.587-592
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by simplex method in reconstructive search space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.241-244
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• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide resemblance between individuals and research optimum solutions by single point method in reconstructive research space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• 한국소음진동공학회논문집
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• 제12권12호
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• pp.935-942
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• 2002

When designing fluid mounts, design parameters can be varied in order to obtain a desired notch frequency and notch depth. The notch frequency is a function of the mount parameters and is typically selected by the designer to occur at the vibration disturbance frequency. Since the process of choosing these parameters can involve some trial and error, it seems to be a great application for obtaining optimal performance of the mount. Many combinations of parameters are possible to give us the desired notch frequency, but the question is which combination provides the lowest depth. Therefore. an automatic optimal technique is needed to optimize the performance of the fluid mount. In this study. the enhanced genetic algorithm (EGA) is applied to minimizing transmissibility of a fluid mount at the desired notch frequency, and at the notch and resonant frequencies. The EGA is modified genetic algorithm to search global and local optimal solutions of multi-modal function optimization. Furthermore. to reduce the searching time as compare to conventional genetic algorithm and Increase the precision of the solutions, the modified simplex method is combined with the algorithm. The results show that the performance of the optimized mount by using the hybrid algorithm is better than that of the conventional fluid mount.

• 한국지능시스템학회논문지
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• 제11권5호
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• pp.373-378
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• 2001

본 연구에서의 다봉성 함수의 최적화를 위한 향상된 유전알고리듬을 제안하였다. 이 방법은 2개의 주요 단계로 구성된다. 첫째 단계는 유전알고리듬과 함수인정기준을 이용한 전역탐색단계이다. 초기해 집단에 대한 개체군의 소속도를 함수인정기준에 따라 결정한다. 둘째 단계는 개체군과 탐색최적해 사이의 유사도를 결정하고, 재구성된 탐색공간에서 단일점 탐색법에 의해 최적해를 탐색한다. 4개의 시험함수를 이용한 수치 예에 대해 종래의 방법과의 비교를 통하여 제안된 알고리듬이 모든 전역최적해 뿐만 아니라 국부최적해도 탐색이 가능함을 확인하였다.

• 대한토목학회논문집
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• 제32권6A호
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• pp.369-378
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• 2012

이 연구에서는 풍력 터빈 블레이드의 형상 최적화를 위한 직접탐색 기반의 최적화 기법을 적용하고, 최적화 기법간의 성능을 비교하여 효과적인 방법을 제안하고자 하였다. 이를 위하여 수평축 풍력 터빈의 최적설계 코드인 HARP_Opt(Horizontal Axis Rotor Performance Optimizer)을 기반으로 연간 발전량 평가 방법을 수정하고, HARP_Opt에서 적용하고 있는 기존의 유전자 알고리즘과 함께 패턴 서치 방법을 추가 적용하였다. 이를 1MW급 풍력 발전 터빈 블레이드의 단면 형상 최적 설계 문제에 적용하였으며, 기존의 유전자 알고리즘 및 마이크로 유전자 알고리즘, 그리고 패턴 서치 방법의 성능을 비교한 결과, 연간 발전량과 해의 일관성 면에 있어서는 패턴 서치 방법이 상대적으로 우수하였으며, 계산시간 측면에서는 마이크로 유전자 알고리즘이 상대적으로 우수한 것으로 분석되었다.

• 대한기계학회논문집A
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• 제26권2호
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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.

• 대한기계학회논문집A
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• 제26권6호
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• pp.1008-1015
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• 2002

This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.