• Title/Summary/Keyword: NSGA II

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Multi-Objective Optimization of a Dimpled Channel Using NSGA-II (NSGA-II를 통한 딤플채널의 다중목적함수 최적화)

  • Lee, Ki-Don;Samad, Abdus;Kim, Kwang-Yong
    • 한국전산유체공학회:학술대회논문집
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    • 2008.03b
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    • pp.113-116
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    • 2008
  • This work presents numerical optimization for design of staggered arrays of dimples printed on opposite surfaces of a cooling channel with a fast and elitist Non-Dominated Sorting of Genetic Algorithm (NSGA-II) of multi-objective optimization. As Pareto optimal front produces a set of optimal solutions, the trends of objective functions with design variables are predicted by hybrid multi-objective evolutionary algorithm. The problem is defined by three non-dimensional geometric design variables composed of dimpled channel height, dimple print diameter, dimple spacing and dimple depth to maximize heat transfer rate compromising with pressure drop. Twenty designs generated by Latin hypercube sampling were evaluated by Reynolds-averaged Navier-Stokes solver and the evaluated objectives were used to construct Pareto optimal front through hybrid multi-objective evolutionary algorithm. The optimum designs were grouped by k-mean clustering technique and some of the clustered points were evaluated by flow analysis. With increase in dimple depth, heat transfer rate increases and at the same time pressure drop also increases, while opposite behavior is obtained for the dimple spacing. The heat transfer performance is related to the vertical motion of the flow and the reattachment length in the dimple.

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Optimization of Vacuum Cleaner Handle Using Approximate Model and NSGA-II (근사 모델과 NSGA-II를 이용한 진공청소기 손잡이 근사최적설계)

  • Yun, Minro;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.26 no.1
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    • pp.30-35
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    • 2017
  • The major parts of a vacuum cleaner are molded. The vacuum cleaner works in multi-load conditions. Therefore, the designer needs to optimize the structure and injection molding conditions simultaneously. Here, the main factor of design is the rib shape and thickness. The greater the rib thickness, the greater the stiffness of the structure. However, it causes an increase in weight. On the other hand, the lower the rib thickness, the greater the increase in the injection pressure. However, the weight will be reduced. Therefore, the designer needs to optimize the rib shape and thickness for structure stiffness and injection molding. In order to solve this problem, we propose an optimization method using D.O.E and a response surface model, which is a multi-objective optimization method using the multi-objective genetic algorithm.

An Optimization Framework for Solving Sequential HW/SW Partitioning Problems (순차적 하드웨어/소프트웨어 파티셔닝 문제들을 해결하기위한 최적화 프레임워크)

  • Lee, Soo-Jung;Chang, Hyeong-Soo
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06b
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    • pp.470-473
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    • 2011
  • 본 논문에서는 첫째, 기존 HW/SW partitioning문제의 접근 방식 모델에서 다루지 못하였던 시간 의존적인 개발 기간, 판매 가격, 판매량, time-to-market 등의 요소들을 반영하는 multi-objective 최적화문제 형태의 새로운 "Sequential HW/SW Partitioning Optimization Framework(SPOF)"를 제시하고 둘째, 그 모델로 형식화된 NP-hard 문제를 일반적으로 해결하기위한 해법으로 SPOF의 형태에 맞게끔 변형한 chromosome과 genetic operation을 사용하는 메타휴리스틱 "Fast and Elitist Multi-objective Genetic Algorithm(NSGA-II)"을 제시한다. 실험을 통하여 NSGA-II의 최적 솔루션에의 수렴성을 보인다.

Approximate Multi-Objective Optimization of Bike Frame Considering Normal Load (수직하중을 고려한 자전거 프레임의 다중목적 최적설계)

  • Chae, Yunsik;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.2
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    • pp.211-216
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    • 2015
  • Recently, because of the growth in the leisure industry and interest in health, the demand for bicycles has increased. In this research, considering the vertical load on a bike frame under static state conditions, the deflection and mass of the bike frame were minimized by satisfying the service condition and performing optimization. The thickness of the bicycle-frame tube was set to a design variable, and its sensitivity was confirmed by an analysis of means (ANOM). To optimize the solution, a response-surface-method (RSM) model was constructed using D-Optimal and central composite design(CCD). The optimization was performed using a non-dominant sorting genetic algorithm (NSGA-II), and the optimal solution was verified by finite-element analysis.

Approximate Multi-Objective Optimization of Stiffener of Steel Structure Considering Strength Design Conditions (강도조건을 고려한 강구조물 보강재의 다목적 근사최적설계)

  • Jeon, Eungi;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.2
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    • pp.192-197
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    • 2015
  • In many fields, the importance of reducing weight is increasing. A product should be designed such that it is profitable, by lowering costs and exhibiting better performance than other similar products. In this study, the mass and deflection of steel structures have to be reduced as objective functions under constraint conditions. To reduce computational analysis time, central composite design(CCD) and D-Optimal are used in design of experiments(DOE). The accuracy of approximate models is evaluated using the $R^2$ value. In this study, the objective functions are multiple, so the non-dominant sorting genetic algorithm(NSGA-II), which is highly efficient, is used for such a problem. In order to verify the validity of Pareto solutions, CAE results and Pareto solutions are compared.

Approximate Optimization Design Considering Automotive Wheel Stress (자동차용 휠의 응력을 고려한 근사 최적 설계)

  • Lee, Hyunseok;Lee, Jongsoo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.3
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    • pp.302-307
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    • 2015
  • The automobile is an important means of transportation. For this reason, the automotive wheel is also an important component in the automotive industry because it acts as a load support and is closely related to safety. Thus, the wheel design is a very important safety aspect. In this paper, an optimal design for minimizing automotive wheel stress and increasing wheel safety is described. To study the optimal design, a central composite design (CCD) and D-optimal design theory are applied, and the approximate function using the response surface method (RSM) is generated. The optimal solutions using the non-dominant sorting genetic algorithm (NSGA-II) are then derived. Comparing CCD and D-optimal solution accuracy and verified the CCD can deduce more accuracy optimal solutions.

Weighted sum Pareto optimization of a three dimensional passenger vehicle suspension model using NSGA-II for ride comfort and ride safety

  • Bagheri, Mohammad Reza;Mosayebi, Masoud;Mahdian, Asghar;Keshavarzi, Ahmad
    • Smart Structures and Systems
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    • v.22 no.4
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    • pp.469-479
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    • 2018
  • The present research study utilizes a multi-objective optimization method for Pareto optimization of an eight-degree of freedom full vehicle vibration model, adopting a non-dominated sorting genetic algorithm II (NSGA-II). In this research, a full set of ride comfort as well as ride safety parameters are considered as objective functions. These objective functions are divided in to two groups (ride comfort group and ride safety group) where the ones in one group are in conflict with those in the other. Also, in this research, a special optimizing technique and combinational method consisting of weighted sum method and Pareto optimization are applied to transform Pareto double-objective optimization to Pareto full-objective optimization which can simultaneously minimize all objectives. Using this technique, the full set of ride parameters of three dimensional vehicle model are minimizing simultaneously. In derived Pareto front, unique trade-off design points can selected which are non-dominated solutions of optimizing the weighted sum comfort parameters versus weighted sum safety parameters. The comparison of the obtained results with those reported in the literature, demonstrates the distinction and comprehensiveness of the results arrived in the present study.

Methodology for Optimizing Permittivity Distribution of 145 kV Miniaturized Functional Graded Spacer Using Non-Dominated Sorting Genetic Algorithm-II (비지배 정렬 유전 알고리즘-II를 이용한 145 kV급 축소형 경사기능성 적용 스페이서의 유전율 분포 최적화 방법론)

  • Noh, Yo-Han;Kim, Seung-Hyun;Cheong, Jong-Hun;Cho, Han-Goo
    • Journal of the Korean Institute of Electrical and Electronic Material Engineers
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    • v.33 no.3
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    • pp.225-230
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    • 2020
  • Recently, with the miniaturization of GIS, there is a need for the miniaturization of spacers as accessories. Miniaturized spacers make it difficult to secure adequate insulation distances, resulting in a more concentrated electric field at the triple junction of high-voltage (HV) conductor-insulator (spacer)-insulation gas (SF6), which is a weakness in GIS. Therefore, by introducing a new concept design technology, functionally graded material (FGM), which is recently applied to various materials and parts industries, three-dimensional control of the dielectric constant distribution in a spacer can be expected to alleviate triple-junction electric field occupancy and improve insulation performance. In this study, we propose an optimized model using NSGA-II to optimize the permittivity distribution of FGM applied spacer.

Resource Allocation for Relay-Aided Cooperative Systems Based on Multi-Objective Optimization

  • Wu, Runze;Zhu, Jiajia;Hu, Hailin;He, Yanhua;Tang, Liangrui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2177-2193
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    • 2018
  • This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

A Proposal of Model Updating Method for Steel Frame Using Global/Local Responses (전역적/국부 응답을 이용한 철골조의 모델 업데이팅 기법 제안)

  • Oh, Byung-Kwan;Choi, Se-Woon;Kim, Yousok;Park, Hyo-Seon
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.28 no.4
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    • pp.401-408
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    • 2015
  • Conventional model updating methods for the structures have used global structural responses which are modal parameters obtained through vibration measurements. Although models updated by modal parameters estimate global structural responses accurately, they have difficulties to predict local responses for safety assesment of structural members. The safety of structural members in the structures has been evaluated through the stress estimation based on strain measurements. Thus, this study additionally uses measured strain responses of structural members to perform model updating besides modal parameters. In the proposed method, the objective functions are set to the differences of the global and local responses obtained from updated model and measurement and those functions are minimized by NSGA-II, one of the multi-objective optimization techniques. The strain responses predicted from updated model are used for safety assessment of the steel frame structures. The proposed method are verified by numerical and experimental studies through the impact hammer tests for a steel frame specimen.