• Title/Summary/Keyword: Optimum Algorithm

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A Study on the Modified Queue Management Scheme for Congestion Avoidance (폭주회피를 위한 개선된 큐 관리 기법에 관한 연구)

  • 양진영;이팔진;김종화
    • Journal of Internet Computing and Services
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    • v.2 no.2
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    • pp.65-70
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    • 2001
  • In this paper, a Modified RED algorithm for congestion avoidance in IP networks is presented. The RED detects incipient congestion by computing the average queue size. By notifying only a randomly selected fraction of connection, it causes to the global synchronization or fairness problem, And also, the network characteristics need to be known in order to find th optimum average queue length. When the average queue size exceeds a minimum threshold, a modified RED algorithm drops packets based on the state of each connection. Performance is improved because of keeping the average queue size low while allowing occasional bursts of packets in the queue, we compare performance of modified RED with RED and Drop Tail in terms of goodput, network utilization and fairness.

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Aerodynamic Design of Helicopter Rotor Airfoil in Forward Flight Using Response Surface Method (반응표면법을 이용한 전진비행하는 헬리콥터 로터 에어포일의 공력설계)

  • Sun, Hyo-Sung;Lee, Soo-Gab
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.32 no.7
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    • pp.13-18
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    • 2004
  • This paper describes an efficient and robust optimization method for helicopter rotor airfoil design in forward flight. Navier-Stokes analysis was employed to compute the dynamic response of an airfoil, which simulates the unsteady rotor flow-field in forward flight. The optimization system consists of two categories; Response Surface Method to construct the response surface model based on D-optimal 3-level factorial design, and Genetic Algorithm to obtain the optimum solution of a defined objective function including penalty terms of constraints. The influence of design variables and their interactions on the aerodynamic performance was examined through the optimization process.

Elite-initial population for efficient topology optimization using multi-objective genetic algorithms

  • Shin, Hyunjin;Todoroki, Akira;Hirano, Yoshiyasu
    • International Journal of Aeronautical and Space Sciences
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    • v.14 no.4
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    • pp.324-333
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    • 2013
  • The purpose of this paper is to improve the efficiency of multi-objective topology optimization using a genetic algorithm (GA) with bar-system representation. We proposed a new GA using an elite initial population obtained from a Solid Isotropic Material with Penalization (SIMP) using a weighted sum method. SIMP with a weighted sum method is one of the most established methods using sensitivity analysis. Although the implementation of the SIMP method is straightforward and computationally effective, it may be difficult to find a complete Pareto-optimal set in a multi-objective optimization problem. In this study, to build a more convergent and diverse global Pareto-optimal set and reduce the GA computational cost, some individuals, with similar topology to the local optimum solution obtained from the SIMP using the weighted sum method, were introduced for the initial population of the GA. The proposed method was applied to a structural topology optimization example and the results of the proposed method were compared with those of the traditional method using standard random initialization for the initial population of the GA.

Stator Slot Shape Optimization of Induction Motors for Iron Loss Reduction (철손 저감을 위한 유도전동기 고정자 슬롯 형상 최적화)

  • Park, S.B.;Lee, H.B.;Park, I.H.;Chung, T.K.;Hahn, S.Y.
    • Proceedings of the KIEE Conference
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    • 1994.07a
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    • pp.150-152
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    • 1994
  • In this paper, the optimum shape design of stator slot of induction motors for iron loss reduction is proposed. To obtain the flux distribution in induction motors, 2-D finite element method with voltage source is employed. The iron loss is calculated from the iron loss data given by the iron manufacturer. To calculate the sensitivity of iron loss to shape variation, the sensitivity analysis of discrete approach is used. The proposed algorithm is applied to a 3-phase squirrel cage induction motor. The nodes at stator slot boundary of the induction motor are defined as design parameters. By controlling these parameters under the constant volume of iron, we can minimize the iron loss. Furthermore, the stator copper loss is reduced by increasing the slot area. So the stator slot area is determined at the point that the summation of iron loss and copper loss of stator is minimized. Since the constraint of constant volume of iron is nonlinear to the design parameters, the Gradient Projection method is used as an optimization algorithm.

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Development of a Heuristic Method for Solving a Class of Nonlinear Integer Programs with Application to Redundancy Optimization for the Safely Control System using Multi-processor (비선형정수계획의 새로운 발견적해법의 개발과 고성능 다중프로세서를 이용한 안전관리 시스템의 신뢰도 중복설계의 최적화)

  • 김장욱;김재환;황승옥;박춘일;금상호
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.1 no.2
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    • pp.69-82
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    • 1995
  • This study is concerned with developing a heuristic algorithm for solving a class of ninlinear integer programs(NLIP). Exact algrithm for solving a NLIP either may not exist, or may take an unrealistically large amount of computing time. This study develops a new heuristic, the Excursion Algorithm(EA), for solving a class of NLIP's. It turns out that excursions over a bounded feasible and/or infeasible region is effective in alleviation the risks of being trapped at a lical optimum. The developed EA is applied to the redundancy optimization problems for improving the system safety, and is compared with other existing heuristic methods. We also include simulated annealing(SA) method in the comparision experiment due to ist populatrity for solving complex combinatorial problems. Computational results indicate that the proposed EA performs consistently better than the other in terms of solution quality, with moderate increase in computing time. Therefore, the proposed EA is believed to be an attractive alternative to other heuristic methods.

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A developed design optimization model for semi-rigid steel frames using teaching-learning-based optimization and genetic algorithms

  • Shallan, Osman;Maaly, Hassan M.;Hamdy, Osman
    • Structural Engineering and Mechanics
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    • v.66 no.2
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    • pp.173-183
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    • 2018
  • This paper proposes a developed optimization model for steel frames with semi-rigid beam-to-column connections and fixed bases using teaching-learning-based optimization (TLBO) and genetic algorithm (GA) techniques. This method uses rotational deformations of frame members ends as an optimization variable to simultaneously obtain the optimum cross-sections and the most suitable beam-to-column connection type. The total cost of members plus connections cost of the frame are minimized. Frye and Morris (1975) polynomial model is used for modeling nonlinearity of semi-rigid connections, and the $P-{\Delta}$ effect and geometric nonlinearity are considered through a stepped analysis process. The stress and displacement constraints of AISC-LRFD (2016) specifications, along with size fitting constraints, are considered in the design procedure. The developed model is applied to three benchmark steel frames, and the results are compared with previous literature results. The comparisons show that developed model using both LTBO and GA achieves better results than previous approaches in the literature.

Optimal placement of piezoelectric curve beams in structural shape control

  • Wang, Jian;Zhao, Guozhong;Zhang, Hongwu
    • Smart Structures and Systems
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    • v.5 no.3
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    • pp.241-260
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    • 2009
  • Shape control of flexible structures using piezoelectric materials has attracted much attention due to its wide applications in controllable systems such as space and aeronautical engineering. The major work in the field is to find a best control voltage or an optimal placement of the piezoelectric actuators in order to actuate the structure shape as close as possible to the desired one. The current research focus on the investigation of static shape control of intelligent shells using spatially distributed piezoelectric curve beam actuators. The finite element formulation of the piezoelectric model is briefly described. The piezoelectric curve beam element is then integrated into a collocated host shell element by using nodal displacement constraint equations. The linear least square method (LLSM) is employed to get the optimum voltage distributions in the control system so that the desired structure shape can be well matched. Furthermore, to find the optimal placement of the piezoelectric curve beam actuators, a genetic algorithm (GA) is introduced in the computation model as well as the consideration of the different objective functions. Numerical results are given to demonstrate the validity of the theoretical model and numerical algorithm developed.

Topology Optimization of Shell Structures Using Adaptive Inner-Front(AIF) Level Set Method (적응적 내부 경계를 갖는 레벨셋 방법을 이용한 쉘 구조물의 위상최적설계)

  • Park, Kang-Soo;Youn, Sung-Kie
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.157-162
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    • 2007
  • A new level set based topology optimization employing inner-front creation algorithm is presented. In the conventional level set based topology optimization, the optimum topology strongly depends on the initial level set distribution due to the incapability of inner-front creation during optimization process. In the present work, in this regard, an inner-front creation algorithm is proposed. in which the sizes. shapes. positions, and number of new inner-fronts during the optimization process can be globally and consistently identified by considering both the value of a given criterion for inner-front creation and the occupied volume (area) of material domain. To facilitate the inner-front creation process, the inner-front creation map which corresponds to the discrete valued criterion of inner-front creation is applied to the level set function. In order to regularize the design domain during the optimization process, the edge smoothing is carried out by solving the edge smoothing partial differential equation (PDE). Updating the level set function during the optimization process, in the present work, the least-squares finite element method (LSFEM) is employed. As demonstrative examples for the flexibility and usefulness of the proposed method. the level set based topology optimization considering lightweight design of 3D shell structure is carried out.

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An Algorithm for the Optimum Separation of Superimposed EMG Signal Using Wavelet Filter (웨이브렛 필터를 이용한 복합 중첩 근신호의 최적화 분리 알고리즘)

  • 이영석;김성환
    • Journal of Biomedical Engineering Research
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    • v.17 no.3
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    • pp.319-326
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    • 1996
  • Clinical myography(EMG) is a technique for diagnosing neuromuscular disorders by analyzing the electrical signal that can be records by needle electrode during a muscular contraction. The EMG signal arises from electrical discharges that accompany the generation of force by groups of muscular fiber, and the analysis of EMG signal provides symptoms that can distinguish disorder of mLecle from disor- ders of nerve. One of the methods for analysis of EMG signal is to separate the individual discharge-the motor unit action potentials(MVAPS) - from EMG signal. But we can only observe the EMG signal that is a superimposed version of time delayed MUAPS. To obtain the information about MUAP(, i.e., position, firing number, magnitude etc), first of all, a method that can separate each MUAP from the EMG signal must be developed Although the methods for MUAP separation have been proposed by many researcherl they have required heavy computational burden. In this paper, we proposed a new method that has less computational burden and performs more reliable separation of superimposed EMG signal using wavelet filter which has multiresolution analysis as major property. As a result, we develope the separation algorithm of superimposed EMG signal which has less computational burden than any other researchers and exacutes exact separation process. The performance of this method has been discussed in the automatic resolving procedure which is neccessary to identify every firing of every motor unit from the EMG pattern.

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Topology Optimization of Muffler Hole using Genetic Algorithm (유전자 알고리즘을 이용한 머플러 구멍 위상최적설계)

  • Wang, Semyung;Dikec, Altay;Hwang, Insoo;Kwon, Byoungha
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.1205-1205
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    • 2003
  • Rotary compressors are one of the most important parts of air-conditioners in the industry This device usually has noise problems during the circulation process of the refrigerant and muffler is used for the noise reduction. The acoustic performance of the muffler depends on its shape and its hole locations on the upper surface. Therefore finding the optimum location of the muffler holes is a topic of increasing importance in the compressor industry. In this research the optimization of the muffler hole locations and the importance of the resonator cavity on the lower surface of the muffler in acoustic point of view is studied. At first, the topology optimization for the 2 hole muffler is performed based on a model without resonator cavity by using genetic algorithm. The 2 hole muffler's acoustic analysis and experiment results are matching, however, the optimized model's results are not. By adding the resonator cavity and also by changing the cavity shape, the acoustic analysis and experiment result comparison is Performed for different cavity shapes. The topology optimization of the revised model with cavity is carried out for noise reduction. Finally, the optimized design is produced and tested for validation.

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