• Journal of Electrical Engineering and Technology
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• 제7권2호
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• pp.212-220
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• 2012

In the current paper, the optimization shape of a polysilicon variable-capacitance micromotor (VCM) was determined using the seeker optimization algorithm (SOA). The optimum goal of the algorithm was to find the maximum torque value and minimum ripple torque by varying the geometrical parameters. The optimization process was performed using a combination of SOA and the finite-element method (FEM). The fitness value was calculated via FEM analysis using COMSOL3.4, and SOA was realized by MATLAB7.4. The proposed method was applied to a VCM with eight and six poles at the stator and rotor, respectively. For comparison, this optimization was also performed using the genetic algorithm. The results show that the optimized micromotor using SOA had a higher torque value and lower torque ripple, indicating the validity of this methodology for VCM design.

• 한국지능시스템학회논문지
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• 제18권3호
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• pp.392-400
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• 2008

This paper proposes a novel optimization algorithm inspired by bacteria behavior patterns for foraging. Most bacteria can trace attractant chemical molecules for foraging. This tracing capability of bacteria called chemotaxis might be optimized for foraging because it has been evolved for few millenniums. From this observation, we developed a new optimization algorithm based on the chemotaxis of bacteria in this paper. We first define behavior and decision rules based on the behavior patterns of bacteria and then devise an optimization algorithm with these behavior and decision rules. Generally bacteria have a quorum sensing mechanism that makes it possible to effectively forage, but we leave its implementation as a further work for simplicity. Thereby, we call our algorithm a simple bacteria cooperative optimization (BCO) algorithm. Our simple BCO is tested with four function optimization problems on various' parameters of the algorithm. It was found from experiments that the simple BCO can be a good framework for optimization.

• 대한건축학회논문집:구조계
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• 제35권10호
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• pp.135-142
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• 2019

Ant colony optimization(ACO) technique is utilized in truss size optimization with frequency constraints. Total weight of truss to be minimized is considered as the objective function and multiple natural frequencies are adopted as constraints. The modified traveling salesman problem(TSP) is adopted and total length of the TSP tour is interpreted as the weight of the structure. The present ACO-based design optimization procedure uses discrete design variables and the penalty function is introduced to enforce design constraints during optimization process. Three numerical examples are carried out to verify the capability of ACO in truss optimization with frequency constraints. From numerical results, the present ACO is a very effective way of finding optimum design of truss structures in free vibration. Finally, we provide the present numerical results as future reference solutions.

• Structural Engineering and Mechanics
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• 제77권6호
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• pp.779-795
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• 2021

In the recent decades, various optimization algorithms have been considered for the optimization of structures. In this research, a new enhanced algorithm is used for the size and topology optimization of truss structures. This algorithm, which is obtained from the combination of Crow Search Algorithm (CSA) and the Cellular Automata (CA) method, is called CA-CSA method. In the first iteration of the CA-CSA method, some of the best designs of the crow's memory are first selected and then located in the cells of CA. Then, a random cell is selected from CA, and the best design is chosen from the selected cell and its neighborhood; it is considered as a "local superior design" (LSD). In the optimization process, the LSD design is used to modify the CSA method. Numerical examples show that the CA-CSA method is more effective than CSA in the size and topology optimization of the truss structures.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.579-580
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• 2009

Proxy Mobile IPv6에서는 같은 Local Mobility Anchor 내의 다른 Mobile Access Gateway에 있는 Mobile Node들의 패킷 전송에 있어서 발생하는 삼각 라우팅 문제는 여전히 존재한다. 이 문제점을 해결하기 위해 인터넷 드래프트 Liebsch와 Dutta에서 제안된 두 가지 Route Optimization 기법의 동작 과정을 알아보고, 상호 데이터 전송 상황에서 더 나은 성능을 제공하는 Correspondent Route Optimization 기법을 제안한다. 제안한 Route Optimization 기법은 Correspondent Flag를 추가하여 Mobile Access Gateway 간 Corresponding Binding을 완료하여, Route Optimization을 설정한다. 제안한 Correspondent Route Optimization 기법은 기존의 기법보다 상호 데이터 전송 상황에서 Route Optimization에 필요한 메시지 수가 적기 때문에 시그널링 비용이 감소하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 춘계학술발표대회
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• pp.1218-1221
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• 2009

최근 Internet Engineering Task Force에서 표준화가 된 Proxy Mobile IPv6는 기존의 이동성 보장 프로토콜인 Mobile IPv6가 가지는 많은 문제점을 보완했다. 하지만, Proxy Mobile IPv6에서 같은 Local Mobility Anchor 내에 있고, 다른 Mobile Access Gateway에 있는 Mobile Node 사이의 패킷 전송에 있어서 발생하는 삼각 라우팅 문제는 여전히 존재한다. 이 문제점을 해결하기 위해 최근 Liebsch의 드래프트와 A.Dutta의 드래프트에서 제안된 두 가지의 Route Optimization 기법의 동작 과정을 알아보고, 상호 데이터 전송 상황에서 더 나은 성능을 제공하는 새로운 Route Optimization 기법을 제안한다. 제안한 Route Optimization 기법은 Corresponding Information을 이용하여 Mobile Access Gateway 간 Corresponding Binding을 완료하여, Route Optimization을 설정한다. 제안한 Correspondent Information을 이용한 Route Optimization 기법은 기존의 기법보다 상호 데이터 전송 상황에서 Route Optimization에 필요한 메시지 수가 적기 때문에 시그널링 비용이 감소하였다.

• ETRI Journal
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• 제45권1호
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• 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.

• Nuclear Engineering and Technology
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• 제56권2호
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• pp.520-525
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• 2024

The optimization design problem of nuclear reactor radiation shield is a typical multi-objective optimization problem with almost 10 sub-objectives and the sub-objectives are always demanded to be under tolerable limits. In this paper, a design method combining multi-objective optimization algorithms with paralleling discrete ordinate transportation code is developed and applied to shield design of the Savannah nuclear reactor. Three approaches are studied for light-weighted and compact design of radiation shield. Comparing with directly optimization with 10 objectives and the single-objective optimization, the approach by setting sub-objectives representing weight and volume as optimization objectives while treating other sub-objectives as constraints has the best performance, which is more suitable to reactor shield design.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.