• 제어로봇시스템학회논문지
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• 제17권7호
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• pp.619-624
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• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• 한국국방경영분석학회지
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• 제13권1호
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• pp.45-64
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• 1987

Power algorithms for analysis of variance tests are presented. In experimental design of operational tests and evaluations the selection of design parameters so as to attain an experiment with desired power is a difficult and important problem. An interactive computer program is presented which uses the power algorithms for ANOVA tests and creates graphical presentations which can be used to assist decision makers in statistical design. ANOVA tests and associated parameters (such as sample size, types and levels of treatments, and alpha-level)are examined.

• 한국전산구조공학회논문집
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• 제19권4호
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• pp.357-367
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• 2006

재분배 기법은 민감도 해석 없이 변위에 대한 각 부재의 변위기여도를 간단하게 계산 한 후, 변위기여도에 근거하여 물량을 분배함으로서 변위를 제어할 수 있는 실용적인 고층건물 변위 설계법으로 인식되고 있다. 그러나 에너지 이론에 근거한 재분배 기법은 하중 조건에 따라서 서로 다른 변위기여도를 가질 수 있게 되며, 특히 횡력 뿐만 아니라 상당한 량의 연직하중도 함께 받고 있는 고층건물의 재분배 기법 적용시의 변위기여도 계산에는 연직하중의 영향이 고려하여야 한다. 또한, 고층 건물의 변위설계에 재분배 기법을 적용하기 위해서는 실용성을 높이기 위해서 부재 그룹핑이 고려되어지는데 부재 그룹핑 고려에 따른 연직하중의 영향을 다르게 나타나게 된다. 그러므로, 본 연구에서는 하중의 종류와 부재 그룹핑 여부를 변수로 하여 세 가지의 재분배 알고리즘을 개발한 후, 이를 20층 강접 골조 전단벽 예제와 60층 아웃리거 예제의 변위 설계 적용하였다.

• 한국지능시스템학회논문지
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• 제11권7호
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• pp.615-620
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• 2001

This paper addresses the design of sliding model fuzzy-model-based controller using genetic algorithms. In general, the construction of fuzzy logic controllers has difficulties for the lack of systematic design procedure. To release this difficulties, the sliding model fuzzy-model-based controllers was presented by authors. In this proposed method, the fuzzy model, which represents the local dynamic behavior of the given nonlinear system, is utilized to construct the controller. The overall controller consists of the local compensators which compensate the local dynamic linear model and the feed-forward controller which is designed via sliding mode control theory. Although, the stability and the performance is guaranteed by the proposed method, some design parameters have to be chosen by the designer manually. This problem can be solved by using genetic algorithms. The proposed method tunes the parameters of the controller, by which the reasonable accuracy and the control effort is achieved. The validity and the efficiency of the proposed method are verified through simulations.

• 한국해양공학회지
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• 제24권6호
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• pp.109-113
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• 2010

We present the minimum weight optimum design of cross sectional for frame structures subject to natural frequency. The optimum design in this paper employ discrete and continuous design variables and Genetic Algorithms. In this paper, Genetic Algorithms is used in optimization process, and be used the method of Elitism and penalty parameters in order to improved fitness in the reproduction process. For 1-Bay 2-Story frame structure, in examples, continuous and discrete design variables are used, and W-section (No.1~No.64), from AISC, discrete data are used in discrete optimization. In this case, Exhaustive search are used for finding global optimum. Continuous variables are used for 1-Bay 7-Story frame structure. Two typical frame structure optimization examples are employed to demonstrate the availability of Genetic Algorithms for solving minimum weight optimum of frame structures with fundamental and multi frequency.

• Structural Engineering and Mechanics
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• 제65권3호
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• pp.233-241
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• 2018

In this paper, the Colliding Bodies Optimization (CBO), Enhanced Colliding Bodies Optimization (ECBO) and Vibrating Particles System (VPS) algorithms and the force method are used for the simultaneous analysis and design of truss structures. The presented technique is applied to the design and analysis of some planer and spatial trusses. An efficient method is introduced using the CBO, ECBO and VPS to design trusses having members of prescribed stress ratios. Finally, the minimum weight design of truss structures is formulated using the CBO, ECBO and VPS algorithms and applied to some benchmark problems from literature. These problems have been designed by using displacement method as analyzer, and here these are solved for the first time using the force method. The accuracy and efficiency of the presented method is examined by comparing the resulting design parameters and structural weight with those of other existing methods.

• 한국자동차공학회논문집
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• 제14권1호
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• pp.25-30
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• 2006

This study is about an optimum design to improve the kinematic and compliance characteristics of a torsion-beam suspension system. The kinematic and compliance characteristics of an initial design of the suspension was obtained through a roll-mode analysis. The objective function was set to minimize within design constraints. The coordinates of the connecting point between the torsion-beam and the trailing arm were treated as design parameters. Since the torsion-beam suspension has large nonlinear effects due to kinematic and elastic motion, Genetic Algorithms were employed for the optimal design. The optimized results were verified through a double-lane change simulation using the full vehicle model.

• 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.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.

• 한국경영과학회지
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• 제29권3호
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.