• Title/Summary/Keyword: Multi-objective function optimization

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Optimal Design of an In-Wheel Permanent Magnet Synchronous Motor Using a Design of Experiment and Kriging Model (크리깅 기법을 이용한 휠인 영구자석 동기전동기의 최적 설계)

  • Jang, Eun-Young;Hwang, Kyu-Yun;Rhyu, Se-Hyun;Kwon, Byung-Il
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.852-853
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    • 2008
  • This paper proposes an optimal design method for the shape optimization of the permanent magnets (PM) of an in-wheel permanent magnet synchronous motor (PMSM) to reduce the cogging torque considering a total harmonic distortion (THD) and a root mean square (RMS) value of back-EMF. In this method, the Kriging model based on a design of experiment (DOE) is applied to interpolate the objective function in the spaces of design parameters. The optimal design method for the PM of an in-wheel PMSM has to consider multi-variable and multi-objective functions. The developed design method is applied to the optimization for the PM of an in-wheel PMSM.

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Optimization of Multi-objective Function based on The Game Theory and Co-Evolutionary Algorithm (게임 이론과 공진화 알고리즘에 기반한 다목적 함수의 최적화)

  • 김지윤;이동욱;심귀보
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.395-398
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    • 2002
  • 본 논문에서는 ‘다목적 함수 최적화 문제(Multi-objective Optimization Problem MOP)’를 풀기 위하여 유전자 알고리즘을 진화적 게임 이론 적용시킨 ‘내쉬 유전자 알고리즘(Nash GA)’과 본 논문에서 새로이 제안하는 공진화 알고리즘의 구조를 설명하고 이 두 알고리즘의 결과를 시뮬레이션을 통하여 비교 검토함으로써 ‘진화적 게임 이론(Evolutionary Game Theory : EGT)’의 두 가지 아이디어 -‘내쉬의 균형(Equilibrium)’과 ‘진화적 안정전략(Evolutionary Stable Strategy . ESS)’-에 기반한 최적화 알고리즘들이 다목적 함수 문제의 최적해를 탐색할 수 있음을 확인한다.

Optimal Controller Design for Single-Phase PFC Rectifiers Using SPEA Multi-Objective Optimization

  • Amirahmadi, Ahmadreza;Dastfan, Ali;Rafiei, Mohammadreza
    • Journal of Power Electronics
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    • v.12 no.1
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    • pp.104-112
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    • 2012
  • In this paper a new method for the design of a simple PI controller is presented and it has been applied in the control of a Boost based PFC rectifier. The Strength Pareto evolutionary algorithm, which is based on the Pareto Optimality concept, used in Game theory literature is implemented as a multi-objective optimization approach to gain a good transient response and a high quality input current. In the proposed method, the input current harmonics and the dynamic response have been assumed as objective functions, while the PI controller's gains of the PFC rectifier (Kpi, Tpi) are design variables. The proposed algorithm generates a set of optimal gains called a Pareto Set corresponding to a Pareto Front, which is a set of optimal results for the objective functions. All of the Pareto Front points are optimum, but according to the design priority objective function, each one can be selected. Simulation and experimental results are presented to prove the superiority of the proposed design methodology over other methods.

Design of RCGA-based PID controller for two-input two-output system

  • Lee, Yun-Hyung;Kwon, Seok-Kyung;So, Myung-Ok
    • Journal of Advanced Marine Engineering and Technology
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    • v.39 no.10
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    • pp.1031-1036
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    • 2015
  • Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

A Multi-Point Design Optimization of a Space Launcher Nose Shapes Using Response Surface Method (반응면 기법을 이용한 발사체 선두부 다점 최적설계)

  • Kim Sang-Jin;Seon Yong-Hee;Lee Jae-Woo;Byun Yung-Hwan
    • 한국전산유체공학회:학술대회논문집
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    • 2000.10a
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    • pp.46-53
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    • 2000
  • To improve the performance at all design points, multi-point optimization method is implemented for the nose fairing shape design of space launcher. The response surface method is used to effectively reduce the huge computational loads during the optimization process. The drag is selected as the objective function, and the surface heat transfer characteristics, and the internal volume of the nose fairing ate considered as design constraints. Full Wavier-Stokes equations are selected as governing equations. Two points drag minimization, and two points drag / heat flux optimization were successfully performed and configurations which have good performance for the wide operation range were derived. By considering three design points, the space launcher shape which undergoes the least drag during whole flight mission was designed. For all the design cases, the constructed response surfaces show good confidence level with only 23 design points with the proper stretching of the design space.

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Back Analysis of the Earth Wall in Multi-layered Subgrade (다층지반에 근입된 흙막이 벽의 역해석에 관한 연구)

  • 이승훈;김종민;김수일;장범수
    • Journal of the Korean Geotechnical Society
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    • v.18 no.1
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    • pp.71-78
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    • 2002
  • This paper presents a back-calculation technique leer the prediction of the behavior of earth wall inserted in multi-layered soil deposit. The soil properties are back-calculated from the measured displacement at each construction stage and the behavior of earth wall far the next construction stage is predicted using back-calculated soil properties. For multi-layered soil deposit, the back-calculation would be very difficult due to the increase in the number of variables. In this study, to solve this difficulty, the back-calculation was performed successively from the lowest layer to the upper layers. An efficient elasto-plastic beam-column analysis was used for forward analysis to minimize the computation time of iterative back-calculation procedure. The coefficients of subgrade reaction and lateral earth pressure necessary for the formation of p-y curve were selected as back calculation variables, and to minimize the effect of abnormal behavior of the wall which might be caused by any unexpected action during construction, the difference between measured displacement increment and computed displacement increment at each construction stages is used as the objective function of optimization. The constrained sequential linear programming was used for the optimization technique to found values of variables minimizing the objective function. The proposed method in this study was verified using numerically generated data and measured field data.

Multi Agents-Multi Tasks Assignment Problem using Hybrid Cross-Entropy Algorithm (혼합 교차-엔트로피 알고리즘을 활용한 다수 에이전트-다수 작업 할당 문제)

  • Kim, Gwang
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.4
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    • pp.37-45
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    • 2022
  • In this paper, a multi agent-multi task assignment problem, which is a representative problem of combinatorial optimization, is presented. The objective of the problem is to determine the coordinated agent-task assignment that maximizes the sum of the achievement rates of each task. The achievement rate is represented as a concave down increasing function according to the number of agents assigned to the task. The problem is expressed as an NP-hard problem with a non-linear objective function. In this paper, to solve the assignment problem, we propose a hybrid cross-entropy algorithm as an effective and efficient solution methodology. In fact, the general cross-entropy algorithm might have drawbacks (e.g., slow update of parameters and premature convergence) according to problem situations. Compared to the general cross-entropy algorithm, the proposed method is designed to be less likely to have the two drawbacks. We show that the performances of the proposed methods are better than those of the general cross-entropy algorithm through numerical experiments.

Topology Optimization of Plane Structures with Multi-Frequency Cases (다진동수를 고려한 평면구조물의 위상최적화)

  • Lee, Sang-Jin;Bae, Jung-Eun;Park, Gyeong-Im
    • Proceeding of KASS Symposium
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    • 2006.05a
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    • pp.233-238
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    • 2006
  • This paper provides a new topology optimization technique which is intended to maximize the fundamental frequency with simultaneous consideration of other natural frequencies in the form of multi-frequency problems. The modal strain energy is considered as the objective function to be minimized and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. From numerical tests, the proposed technique is found to be very effective to maximize the fundamental frequency of the structure and it can also successfully consider several higher mode effects into the optimum topology of structure through the introduction of weights.

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Study on a Robust Optimization Algorithm Using Latin Hypercube Sampling Experiment and Multiquadric Radial Basis Function (Latin Hypercube Sampling Experiment와 Multiquadric Radial Basis Function을 이용한 최적화 알고리즘에 대한 연구)

  • Zhang, Yanli;Yoon, Hee-Sung;Koh, Chang-Seop
    • Proceedings of the KIEE Conference
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    • 2007.04c
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    • pp.162-164
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    • 2007
  • This paper presents a "window-zoom-out" optimization strategy with relatively fewer sampling data. In this method, an optimal Latin hypercube sampling experiment based on multi-objective Pareto optimization is developed to obtain the sampling data. The response surface method with multiquadric radial basis function combined with (1+$\lambda$) evolution strategy is used to find the global optimal point. The proposed method is verified with numerical experiments.

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A Optimization of Butterfly Valve using the Characteristic Function (특성함수를 이용한 Butterfly Valve의 최적설계)

  • Park, Young-Chul;Choi, Jong-Sub;Kang, Jin
    • Journal of Ocean Engineering and Technology
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    • v.19 no.3
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    • pp.59-65
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    • 2005
  • In today's industry, the butterfly valve has been used to control a flow effectively. However, it is difficult to have the existing structural optimization using field analysis from CFD to structure analysis when the structure is influenced by fluid. Therefore, an initial model of this study is to evaluate the stability of the valve using FEM and CFD. And, it selected variable using initial analysis results. Also, it accomplished the shape optimization design using the orthogonal arrangement and characteristic function. Research result, a few experiments showed the optimal results of there dimensional structures to be multi-objective.