• 제목/요약/키워드: local optimization

검색결과 915건 처리시간 0.026초

Physics-based Surrogate Optimization of Francis Turbine Runner Blades, Using Mesh Adaptive Direct Search and Evolutionary Algorithms

  • Bahrami, Salman;Tribes, Christophe;von Fellenberg, Sven;Vu, Thi C.;Guibault, Francois
    • International Journal of Fluid Machinery and Systems
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    • 제8권3호
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    • pp.209-219
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    • 2015
  • A robust multi-fidelity optimization methodology has been developed, focusing on efficiently handling industrial runner design of hydraulic Francis turbines. The computational task is split between low- and high-fidelity phases in order to properly balance the CFD cost and required accuracy in different design stages. In the low-fidelity phase, a physics-based surrogate optimization loop manages a large number of iterative optimization evaluations. Two derivative-free optimization methods use an inviscid flow solver as a physics-based surrogate to obtain the main characteristics of a good design in a relatively fast iterative process. The case study of a runner design for a low-head Francis turbine indicates advantages of integrating two derivative-free optimization algorithms with different local- and global search capabilities.

배전계통 커패시터 설치를 위한 전역적 최적화 기법 (A Global Optimization Technique for the Capacitor Placement in Distribution Systems)

  • 이상봉;김규호;이상근
    • 전기학회논문지
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    • 제57권5호
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    • pp.748-754
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    • 2008
  • The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, a global optimization technique, which employing the chaos search algorithm, is applied to solve optimal capacitor placement problem with reducing computational effort and enhancing global optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

A new PSRO algorithm for frequency constraint truss shape and size optimization

  • Kaveh, A.;Zolghadr, A.
    • Structural Engineering and Mechanics
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    • 제52권3호
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    • pp.445-468
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    • 2014
  • In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

Controller Optimization for Bidirectional Power Flow in Medium-Voltage DC Power Systems

  • Chung, Il-Yop;Liu, Wenxin;Cartes, David A.;Cho, Soo-Hwan;Kang, Hyun-Koo
    • Journal of Electrical Engineering and Technology
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    • 제6권6호
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    • pp.750-759
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    • 2011
  • This paper focuses on the control of bidirectional power flow in the electric shipboard power systems, especially in the Medium-Voltage Direct Current (MVDC) shipboard power system. Bidirectional power control between the main MVDC bus and the local zones can improve the energy efficiency and control flexibility of electric ship systems. However, since the MVDC system contains various nonlinear loads such as pulsed power load and radar in various subsystems, the voltage of the MVDC and the local zones varies significantly. This voltage variation affects the control performance of the bidirectional DC-DC converters as exogenous disturbances. To improve the control performance regardless of uncertainties and disturbances, this paper proposes a novel controller design method of the bidirectional DC-DC converters using $L_1$ control theory and intelligent optimization algorithm. The performance of the proposed method is verified via large-scale real-time digital simulation of a notional shipboard MVDC power system.

Medium optimization for keratinase production by a local Streptomyces sp. NRC 13S under solid state fermentation

  • Shata, Hoda Mohamed Abdel Halim;Farid, Mohamed Abdel Fattah
    • Journal of Applied Biological Chemistry
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    • 제56권2호
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    • pp.119-129
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    • 2013
  • Thirteen different Streptomyces isolates were evaluated for their ability to produce keratinase using chicken feather as a sole carbon and nitrogen sources under solid state fermentation (SSF). Streptomyces sp. NRC 13S produced the highest keratinase activity [1,792 U/g fermented substrate (fs)]. The phenotypic characterization and analysis of 16S rDNA sequencing of the isolate were studied. Optimization of SSF medium for keratinase production by the local isolate, Streptomyces sp. NRC13S, was carried out using the one-variable-at-a-time and the statistical approaches. In the first optimization step, the effect of incubation period, initial moisture content, initial pH value of the fermentation medium, and supplementation of some agro-industrial by-products on keratinase production were evaluated. The strain produced about 2,310 U/gfs when it grew on chicken feather with moisture content of 75% (w/w), feather: fodder yeast ratio of 70:30 (w/w), and initial pH 7 using phosphate buffer after 8 days. Based on these results, the Box-Behnken design and response surface methodology were applied to find out the optimal conditions for the enzyme production. The corresponding maximal production of keratinase was about 2,569.38 U/gfs.

Comparison of Automatic Calibration for a Tank Model with Optimization Methods and Objective Functions

  • Kang, Min-Goo;Park, Seung-Woo;Park, Chang-Eun
    • 한국농공학회지
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    • 제44권7호
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    • pp.1-13
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    • 2002
  • Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

Microcanonical Optimization을 이용한 BDD의 최소화 기법 (A Minimization Technique for BDD based on Microcanonical Optimization)

  • 이민나;조상영
    • 정보처리학회논문지A
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    • 제8A권1호
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    • pp.48-55
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    • 2001
  • Using BDD, we can represent Boolean functions uniquely and compactly, Hence, BDD have become widely used for CAD applications, such as logic synthesis, formal verification, and etc. The size of the BDD representation for a function is very sensitive to the choice of orderings on the input variables. Therefore, it is very important to find a good variable ordering which minimize the size of the BDD. Since finding an optimal ordering is NP-complete, several heuristic algorithms have been proposed to find good variable orderings. In this paper, we propose a variable ordering algorithm based on the $\mu$O(microcanonical optimization). $\mu$O consists of two distinct procedures that are alternately applied : Initialization and Sampling. The initialization phase is to executes a fast local search, the sampling phase leaves the local optimum obtained in the previous initialization while remaining close to that area of search space. The proposed algorithm has been experimented on well known benchmark circuits and shows superior performance compared to a algorithm based on simulated annealing.

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WFSO 알고리즘을 이용한 인공 신경망과 합성곱 신경망의 학습 (Training Artificial Neural Networks and Convolutional Neural Networks using WFSO Algorithm)

  • 장현우;정성훈
    • 디지털콘텐츠학회 논문지
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    • 제18권5호
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    • pp.969-976
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    • 2017
  • 본 논문에서는 최적화 알고리즘으로 개발된 WFSO(Water Flowing and Shaking Optimization) 알고리즘을 사용한 인공신경망 과합성공 신경망의 학습 방법을 제안한다. 최적화 알고리즘은 다수의 후보 해를 기반으로 탐색해 나가기 때문에 일반적으로 속도가 느린 단점이 있으나 지역 최소값에 거의 빠지지 않고 병렬화가 용이하며 미분 불가능한 활성화함수를 갖는 인공신경망 학습도 가능하고 구조와 가중치를 동시에 최적화 할 수 있는 장점이 있다. 본 논문에서는 WFSO 알고리즘을 인공신경망 학습에 적용하는 방법을 설명하고 다층 인공신경망과 합성곱 신경망에서 오류역전파 알고리즘과 성능을 비교한다.

도로의 최적노선대 선정방법 비교 연구 (Comparative Study on Determining Highway Routes)

  • 김관중;장명순
    • 한국도로학회논문집
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    • 제8권4호
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    • pp.159-179
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    • 2006
  • 도로의 구조 시설기준에 관한 규칙과 국도의 노선계획 설계지침에 준하여 실행되는 현행 노선선정방법과, 컴퓨터 발전과 함께 국내외에서 연구되고 있는 선형최적화 모형식으로 사례연구 구간의 도로 노선을 선정하여 노선 특성을 비교 분석해본 결과, 현행 노선선정방법은 단계별, 구간별로 순차적인 노선선정이 이루어지는 국지적 최적을 추구하나, 선형 최적화 모형식 선정방법은 모든 설계요소가 동시에 고려된 체계최적(System Optimal)의 노선탐색 능력이 있는 것으로 분석되었다. 또한 선형최적화 모형에서 기존 설계공종별 실제공사비로 비용함수를 보정하여 노선을 선정한 결과 현실에 부합되게 설계되었으며, 경제성이 높은(B/C=1.66) 대안 노선이 탐색되었다. 선형최적화 설계모형은 터널 종단에서 종단 경사가 변화하는 등 보완될 점이 있음에도 타당성조사와 기본설계단계에서 노선선정 도구로서 설계시간 및 비용단축, 다양한 대안 노선의 검토 등의 많은 장점을 지니고 있음이 확인되었다.

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Performance Comparison of CEALM and NPSOL

  • Seok, Hong-Young;Jea, Tahk-Min
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.169.4-169
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    • 2001
  • Conventional methods to solve the nonlinear programming problem range from augmented Lagrangian methods to sequential quadratic programming (SQP) methods. NPSOL, which is a SQP code, has been widely used to solve various optimization problems but is still subject to many numerical problems such as convergence to local optima, difficulties in initialization and in handling non-smooth cost functions. Recently, many evolutionary methods have been developed for constrained optimization. Among them, CEALM (Co-Evolutionary Augmented Lagrangian Method) shows excellent performance in the following aspects: global optimization capability, low sensitivity to the initial parameter guessing, and excellent constraint handling capability due to the benefit of the augmented Lagrangian function. This algorithm is ...

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