• 한국공작기계학회논문집
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• 제16권5호
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• pp.205-210
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• 2007

The integration method of binary and real encoding in genetic algorithm is proposed to deal with design variables of various types in gear drive design. The method is applied to optimum design of multi-stage gear drive. Integer and Discrete type design variables represent the number of teeth and module, and continuous type design variables represent face width, helix angle and addendum modification factor etc. The proposed genetic algorithm is applied for the gear ratio optimization and the volume optimization(minimization) of multi-stage geared motor which is used in field. In result, the proposed design optimization method shows an effectiveness in optimum design process and the new design has a better results compared with the existing design.

• 한국강구조학회 논문집
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• 제13권5호
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• pp.577-586
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• 2001

이 연구에서는 다 셀계수변수와 다 제약조건으로 구성된 단면 및 시스템 형상을 동시에 고려하는 입체 트러스의 이산화 최적설계 문제를 유전자 알고리즘을 이용하여 체계화하였다. 또한 유전자 알고리즘의 적용방법을 초기화절차 진화적 절차 그리고 유전적 절차로 구성하였다. 초기화 절차에서는 한 세대의 개체 수만큼 염색체를 생성하고 진화적 절차는 구조해석의 결과를 분석하여 적합도를 계산하였다. 그리고 유전적 절차는 복제와 교배 및 돌연변이를 통하여 다음 세대의 유전자를 생성하게 된다. 이렇게 진화적 절차와 유전적 절차를 반복 수행하여 최적 해를 탐색한다. 이 연구에서는 설계자가 궁극적 목표로 하는 구조물의 구조 해석과 단면 및 시스템 형상 최적설계를 동시에 수행할 수 있는 이산화 최적설계 프로그램을 개발하고 설계 예를 들어 비교 고찰하였다.

• Structural Engineering and Mechanics
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• 제26권2호
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• pp.191-210
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• 2007

The three different approaches (reformulations) of evolution strategies (ESs) have been proposed in the literature as extensions of the technique for solving discrete problems. This study implements an extensive research on application, evaluation and comparison of them in discrete optimum design of steel frames. A unified formulation is first developed to explain these approaches, so that differences and similarities between their inherent search mechanisms can clearly be identified. Two examples from practical design of steel frames are studied next to measure their performances in locating the optimum. Extensive numerical experimentations are performed in both examples to facilitate a statistical analysis of their convergence characteristics. The results obtained are presented in the histograms demonstrating the distribution of the best designs located by each approach. In addition, an average improvement of the best design during the course of evolution is plotted in each case to compare their relative convergence rates.

• 대한기계학회논문집A
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• 제27권5호
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• pp.798-806
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• 2003

Structural optimization has been carried out in continuous or discrete design space. Methods for continuous design have been well developed though they are finding the local optima. On the contrary, the existing methods for discrete design are extremely expensive in computational cost or not robust. In this research, an algorithm using tabu search is developed fur the discrete structural designs. The tabu list and the neighbor function of the Tabu concepts are introduced to the algorithm. It defines the number of steps, the maximum number for random searches and the stop criteria. A tabu search is known as the heuristic approach while genetic algorithm and simulated annealing algorithm are attributed to the stochastic approach. It is shown that an algorithm using the tabu search with random moves has an advantage of discrete design. Furthermore, the suggested method finds the reliable optimum for the discrete design problems. The existing tabu search methods are reviewed. Subsequently, the suggested method is explained. The mathematical problems and structural design problems are investigated to show the validity of the proposed method. The results of the structural designs are compared with those from a genetic algorithm and an orthogonal array design.

• 한국해양공학회지
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• 제16권4호
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• pp.25-31
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• 2002

This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.

• Advanced Composite Materials
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• 제18권4호
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• pp.297-314
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• 2009

A design method is proposed to optimize the stacking sequence of laminated composite plates for desired vibration characteristics. The objective functions are the natural frequencies of the laminated plates, and three types of optimization problems are studied where the fundamental frequency and the difference of two adjacent frequencies are maximized, and the difference between the target and actual frequencies is minimized. The design variables are a set of discrete values of fiber orientation angles with prescribed increment in the layers of the plates. The four lamination parameters are used to describe the bending property of a symmetrically laminated plate, and are optimized by a gradient method in the first stage. A new technique is introduced in the second stage to convert from the optimum four lamination parameters into the stacking sequence that is composed of the optimum fiber orientation angles of all the layers. Plates are divided into sub-domains composed of the small number of layers and designed sequentially from outer domains. For each domain, the optimum angles are determined by minimizing the errors between the optimum lamination parameters obtained in the first step and the parameters for all possible discrete stacking sequence designs. It is shown in numerical examples that this design method can provide with accurate optimum solutions for the stacking sequence of vibrating composite plates with various boundary conditions.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1999년도 제30회 추계학술대회
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• pp.167-173
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• 1999

This paper suggests a method to design the deep groove ball bearing for high-load capacity by using a genetic algorithm. The design problem of ball bearings is a typical discrete/continuous optimization problem because the deep groove ball bearing has discrete variables, such as ball size and number of balls. Thus, a genetic algorithm is employed to find the optimum values from a set of discrete design variables. The ranking process is proposed to effectively deal with the constraints in genetic algorithm. Results obtained fer several 63 series deep groove ball bearings demonstrated the effectiveness of the proposed design methodology by showing that the average basic dynamic capacities of optimally designed bearings increase about 9~34% compared with the standard ones.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1999년도 가을 학술발표회 논문집
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• pp.127-134
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• 1999

An optimization algorithm based on Genetic Algorithm(GA) is developed for discrete optimization of reinforced concrete plane frame by constructing databases. Under multiple loading conditions, discrete optimum sets of reinforcements for both negative and positive moments in beams, their dimensions, column reinforcement, and their column dimensions are found. Construction practice is also implemented by linking columns and beams by group ‘Connectivity’between columns located in the same column line is also considered. It is shown that the developed genetic algorithm was able to reach optimum design for reinforced concrete plane frame construction practice.

• 대한조선학회논문집
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• 제42권2호
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• 콘크리트학회지
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• 제5권4호
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• pp.167-178
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• 1993

본 논문의 목적은 R.C.보 최적설계에 이산수학계획법을 적용하여 상세설계를 포함하는 실제설계의 가능성을 연구하기 위한 것이다. 이산최적문제에서 설계변수로는 단면의 총높이, 폭, 유효높이 및 길이방향철근의 단면적 그리고 전단철근의 단면적과 길이 방향철근의 절단점과 같은 상세변수 등이 고려되었다. 목적함수는 경비함수로 취했으며, 제약조건으로는 강도설계법에 의한 설계휨강도, 전단강도, 연성, 사용성, 콘크리트 덮개 및 철근간격, 복부보강 그리고 정착길이와 길이방향철근의 절단점 등에 관한 시방서 요구사항을 고려하여 문제를 형성하였다. 이산변수를 갖는 최적설계를 효율적으로 실행하기 위해 첫째단계에서 Feasible Direction Methed를 이용하여 연속최적해를 구했으며, 둘째단계에서 분기한계법(Branch and bound method)을 이용하여 이산최적해를 얻는 최적화 알고리즘을 제안하였다. 제안된 알고리즘의 신뢰도를 검증하기 위해 2개의 이산설계변수를 갖는 수치예에 적용하여 도해법 및 rounde-up method와 그 결과를 비교하였고, 단순지지된 R.C.보 및 2경간연속 R.C.보에 적용하여 제안된 알고리즘의 신뢰도, 효율성 및 적용성을 입증하였다.