• Journal of Electrical Engineering and Technology
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• 제7권4호
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• pp.493-500
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• 2012

In this paper the performance of meta-heuristics algorithms such as GA (Genetic Algorithm), DE (Differential Evolution), PSO (Particle Swarm Optimization) and SA (Simulated Annealing) for the problem of TTC enhancement using FACTS devices are compared. In addition to that in the assessment procedure of TTC two novel techniques are proposed. First the optimization algorithm which is used for TTC enhancement is simultaneously used for assessment of TTC. Second the power flow is done using Broyden - Shamanski method with Sherman - Morrison formula (BSS). The proposed approach is tested on WSCC 9 bus, IEEE 118 bus test systems and the results are compared with the conventional Repeated Power Flow (RPF) using Newton Raphson (NR) method which indicates that the proposed method provides better TTC enhancement and computational efficacy than the conventional procedure.

• Structural Engineering and Mechanics
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• 제11권2호
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• pp.151-170
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• 2001

With increasing competition, the engineering industry is in need of optimization of designs that would lead to minimum cost or weight. Recent developments in Genetic Algorithms (GAs) makes it possible to model and obtain optimal solutions in structural design that can be put to use in industry. The main objective of this paper is to illustrate typical applications of GAs to practical design of structural systems such as steel trusses, towers, bridges, reinforced concrete frames, bridge decks, shells and layout planning of buildings. Hence, instead of details of GA process, which can be found in the reported literature, attention is focussed on the description of the various applications and the practical aspects that are considered in Genetic Modeling. The paper highlights scope and future directions for wider applications of GA based methodologies for optimal design in practice.

• Journal of Advanced Marine Engineering and Technology
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• 제33권1호
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• pp.19-27
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• 2009

Globally, customer appreciation and demand for quieter products has driven noise control engineers to develop efficient and quieter products in a relatively short time. In the vehicles and ship industry, noise has become an important attribute because of the competitive market and increasing customer awareness. Noise reduction is often achieved through structural modifications by typical approaches. In the present paper, author describes a fundamental study on optimum design of curvature. Bezier curve. and rib attachment to reduce noise from simple panel using a genetic algorithm(GA). The acoustic optimization procedure employed p-FEM for structural analysis, the Rayleigh integral method for acoustic analysis and the GA for searching optimum design. In the optimization procedure. the objective function to be minimized is the average sound power radiated from an objective structure over a given frequency range $0{\sim}300$ Hz.

• 상하수도학회지
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• 제22권1호
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• pp.149-157
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• 2008

The reduction of leakage is a major issue of the South Korea water industry. The inclusion of pressure dependent leakage terms in network analysis allows the application of optimization techniques to identify the most effective means of reducing water leakage in distribution networks. This paper proposes a method to find optimal setting and location of control valve for reducing leakage efficiently. The proposed search method differs from previous methods for addressing optimal valve location problem and improves the GA simulation time with guaranteeing for getting the global optimal solution. The strength of this method has been demonstrated by means of case studies. This allows the procedure of optimization to be more robust and computational efficient.

• 한국정밀공학회지
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• 제16권1호통권94호
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• pp.116-124
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• 1999

In most conventional design optimization of dynamic system, design sensitivities are utilized. However, design sensitivities based optimization method has numbers of drawback. First, computing design sensitivities for dynamic system is mathematically difficult, and almost impossible for many complex problems as well. Second, local optimum is obtained. On the other hand, Genetic Algorithm is the search technique based on the performance of system, not on the design sensitivities. It is the search algorithm based on the mechanics of natural selection and natural genetics. GA search, differing from conventional search techniques, starts with an initial set of random solutions called a population. Each individual in the population is called a chromosome, representing a solution to the problem at hand. The chromosomes evolve through successive iterations, called generations. As the generation is repeated, the fitness values of chromosomes were maximized, and design parameters converge to the optimal. In this study, Genetic Algorithm is applied to the actual dynamic optimization problems, to determine the optimal design parameters of the dynamic system.

• ETRI Journal
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• 제33권1호
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• pp.39-49
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• 2011

A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.

• 한국자동차공학회논문집
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• 제10권4호
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• pp.216-222
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• 2002

Brake Moan is a laud and strong noise occurring at any vehicle speed over 2 mph as a low frequency in below 600Hz. In this study, we targeted to shift the unstable mode that causes the brake moan from the moats frequency range to sufficiently higher frequency range to avoid the moan phenomenon. We simulated the finite element model and found out the nodes in which the brake moan occurs the most and we regarded the boundary and its relationship between the brake pad and the rotor as a spring coefficient k. With the binary set of the spring coefficient k, we finally used genetic algorithm (GA) to get the optimal topology of the brake pad and its shape to avoid the brake moan. The final result remarkably shows that genetic algorithm can be used in topology optimization procedures requiring complex eigenvalue problems.

• Journal of Electrical Engineering and Technology
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• 제5권4호
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• pp.653-665
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• 2010

In this study, we introduce a neurofuzzy approach to the design of fuzzy controllers. The development process exploits key technologies of Computational Intelligence (CI), namely, genetic algorithms (GA) and neurofuzzy networks. The crux of the design methodology deals with the selection and determination of optimal values of the scaling factors of fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out. Next, we form a nonlinear mapping for the scaling factors, which are realized by GA-based neurofuzzy networks by using a fuzzy set or fuzzy relation. The proposed approach is applied to control nonlinear systems like the inverted pendulum. Results of comprehensive numerical studies are presented through a detailed comparative analysis.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.520-525
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• 2003

The determination of unknown parameters in rotating machinery is a difficult task and optimization techniques represent an alternative technique for parameter identification. The Simulated Annealing(SA) and Genetic Algorithm(GA) are powerful global optimization algorithm. This paper proposes new hybrid algorithm which combined GA with SA and local search algorithm for the purpose of parameter identification. Numerical examples are also presented to verify the efficiency of proposed algorithm. And, this paper presents the general methodology based on hybrid algorithm to identify unknown bearing parameters of flexible rotors using measured unbalance responses. Numerical examples are used to ilustrate the methodology used, which is then validated experimentally.

• 대한조선학회논문집
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• 제39권4호
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• pp.60-65
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• 2002

본 연구는 Form Parameter를 만족하는 선형 생성 과정을 최적화 과정으로 취급하였다. 목적함수는 fairness 기준을 도입하고 설계변수는 B-spline 곡선의 조정점으로 하며 제약조건은 설계자에 의해서 주어지는 기하학적 형상으로 하였다. 최적화 방법은 GA(Genetic Algorithm)와 최적성 기준(optimality criteria)을 병행하였다.