• Title/Summary/Keyword: Design Algorithm

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Unified Design Method for Toroidal Transformer and its Optimal Algorithm (토로이드형 변압기의 일관성있는 설계법과 그 최적화 알고리즘)

  • 김주홍;이광직
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.5 no.3
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    • pp.78-83
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    • 1991
  • This study proposes a unified method to design toroidal transformer and its optimal design algorithm. This unified design method was derived from the fundamental equation of power on the basis of electromagnetic energy of a core and the definition of three parameters(K1, K2, KW) that influence the form of a core and the ratio of a core and coil. Accordingly this design method condenses the whole data for design of toroidal transformer to a standard variable which is the inner diameter of a core. The minimal cost, weight and volume values of the transformer were computed by means of the algorithm to search the optimal values of the parameters. Furthermore, through the CAD, the efficiency of this unified design method and optimal algorithm proposed in this paper was confirmed.

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Optimal Design of Submarine Pressure Hull Structures Using Genetic Algorithm (유전 알고리즘을 적용한 잠수함 압력선체 최적 구조설계)

  • Cho, Yoon Sik;Paik, Jeom Kee
    • Journal of the Society of Naval Architects of Korea
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    • v.54 no.5
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    • pp.378-386
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    • 2017
  • In this paper, a method is presented for the optimal design of submarine pressure hull structures by taking advantage of genetic algorithm techniques. The objective functions and design constraints in the process of structural optimization are based on the ultimate limit states of hull structures. One of the benefits associated with the utilization of genetic algorithm is that the optimization process can be completed within short generations of design variables for the pressure hull structure model. Applied examples confirm that the proposed method is useful for the optimal design of submarine pressure hull structures. Details of the design procedure with applied examples are documented. The conclusions and insights obtained from the study are summarized.

OPTIMUM DESIGN OF AN AUTOMOTIVE CATALYTIC CONVERTER FOR MINIMIZATION OF COLD-START EMISSIONS USING A MICRO GENETIC ALGORITHM

  • Kim, Y.D.;Kim, W.S.
    • International Journal of Automotive Technology
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    • v.8 no.5
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    • pp.563-573
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    • 2007
  • Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

Shape Optimization of High Voltage Gas Circuit Breaker Using Kriging-Based Model And Genetic Algorithm (크리깅 메타모델과 유전자 알고리즘을 이용한 초고압 가스차단기의 형상 최적 설계)

  • Kwak, Chang-Seob;Kim, Hong-Kyu;Cha, Jeong-Won
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.2
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    • pp.177-183
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    • 2013
  • We describe a new method for selecting design variables for shape optimization of high-voltage gas circuit breaker using a Kriging meta-model and a genetic algorithm. Firstly we sample balance design variables using the Latin Hypercube Sampling. Secondly, we build meta-model using the Kriging. Thirdly, we search the optimal design variables using a genetic algorithm. To obtain the more exact design variable, we adopt the boundary shifting method. With the proposed optimization frame, we can get the improved interruption design and reduce the design time by 80%. We applied the proposed method to the optimization of multivariate optimization problems as well as shape optimization of a high - voltage gas circuit breaker.

Flow Path Design for Automated Transport Systems in Container Terminals Considering Traffic Congestion

  • Singgih, Ivan Kristianto;Hong, Soondo;Kim, Kap Hwan
    • Industrial Engineering and Management Systems
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    • v.15 no.1
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    • pp.19-31
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    • 2016
  • A design method of the network for automated transporters mounted on rails is addressed for automated container terminals. In the network design, the flow directions of some path segments as well as routes of transporters for each flow requirement must be determined, while the total transportation and waiting times are minimized. This study considers, for the design of the network, the waiting times of the transporters during the travel on path segments, intersections, transfer points below the quay crane (QC), and transfer points at the storage yard. An algorithm, which is the combination of a modified Dijkstra's algorithm for finding the shortest time path and a queuing theory for calculating the waiting times during the travel, is proposed. The proposed algorithm can solve the problem in a short time, which can be used in practice. Numerical experiments showed that the proposed algorithm gives solutions better than several simple rules. It was also shown that the proposed algorithm provides satisfactory solutions in a reasonable time with only average 7.22% gap in its travel time from those by a genetic algorithm which needs too long computational time. The performance of the algorithm is tested and analyzed for various parameters.

Optimum Design of High-Speed, Short Journal Bearings by Enhanced Artificial Life Algorithm (향상된 인공생명 알고리듬에 의한 고속, 소폭 저널 베어링의 최적설계)

  • Yang, Bo-Suk;Song, Jin-Dae
    • Proceedings of the KSME Conference
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    • 2001.11a
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    • pp.698-702
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    • 2001
  • This paper presents a combinatorial method to compute the solutions of optimization problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The hybrid algorithm is not only faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. And the enhanced artificial life algorithm is applied to optimum design of high-speed, short journal bearings and the usefuless is verified through this example.

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Optimal Design of PM Wind Generator using Memetic Algorithm (Memetic Algorithms을 적용한 영구자석 풍력발전기 최적설계)

  • Park, Ji-Seong;Ahn, Young-Jun;Kim, Jong-Wook;Lee, Chel-Gyun;Jung, Sang-Yong
    • Proceedings of the KIEE Conference
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    • 2009.04b
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    • pp.6-8
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    • 2009
  • This paper presents the novel implementation of memetic algorithm with GA (Genetic Algorithm) and MADS (Mesh Adaptive Direct Search), which is applied for optimal design methodology of electric machine. This hybrid algorithm has been developed for obtaining the global optimum rapidly, which is effective for optimal design of electric machine with many local optima and much longer computation time. In particular, the proposed memetic algorithm has been forwarded to optimal design of direct-driven PM wind generator for maximizing the Annual Energy Production (AEP), of which design objective should be obtained by FEA (Finite Element Analysis). After all, it is shown that GA combined with MADS has contributed to reducing the computation time effectively for optimal design of PM wind generator when compared with purposely developed GA implemented with the parallel computing method.

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Design of Algorithm Thinking-Based Software Basic Education for Nonmajors (비전공자를 위한 알고리즘씽킹 기반 소프트웨어 기초교육 설계)

  • PARK, So-Hyun
    • The Journal of Industrial Distribution & Business
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    • v.10 no.11
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    • pp.71-80
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    • 2019
  • Purpose: The purpose of this study is to design the curriculum of Basic College Software Programming to develop creative and logical-thinking. This course is guided by algorithmic thinking and logical thinking that can be solved by computing for problem-solving, and it helps to develop by software through basic programming education. Through the stage of problem analysis, abstraction, algorithm, data structure, and algorithm implementation, the curriculum is designed to help learners experience algorithm problem-solving in various areas to develop diffusion thinking. For Learners aim to achieve the balanced development of divergent and convergent-thinking needed in their creative problem-solving skills. Research design, data and methodology: This study is to design a basic software education for improving algorithm-thinking for non-major. The curriculum designed in this paper is necessary to non-majors students who have completed the 'Creative Thinking and Coding Course' Design Thinking based are targeted. For this, contents were extracted through advanced research analysis at home and abroad, and experts in computer education, computer engineering, SW education, and education were surveyed in the form of quasi-openness. Results: In this study, based on ADD Thinking's algorithm thinking, we divided the unit college majors into five groups so that students of each major could accomplish the goal of "the ability to internalize their own ideas into computing," and extracted and designed different content areas, content elements and sub-components from each group. Through three expert surveys, we established a strategy for characterization by demand analysis and major/textbook category and verified the appropriateness of the design direction to ensure that the subjects and contents of the curriculum are appropriate for each family in order to improve algorithm-thinking. Conclusions: This study helps develop software by enhancing the ability of students who practice various subjects and exercises to explore creative expressions in various areas, such as 'how to think like a computer' that can implement and execute their ideas in computing. And it helps increase the ability to think logical and algorithmic computing based on creative solutions, improving problem-solving ability based on computing thinking and fundamental understanding of computer coding and development of logical thinking ability through programming.

Design Classification and Development of Pattern Searching Algorithm Based on Pattern Design Elements - With focus on Automatic Pattern Design System for Baseball Uniforms Manufactured under Custom-MTM System - (패턴설계요소기반의 디자인 분류 및 패턴탐색 알고리즘개발 - 맞춤양산형 야구복 자동패턴 설계시스템을 위한 -)

  • Kang, In-Ae;Choi, Kueng-Mi;Jun, Jung-Ill
    • Fashion & Textile Research Journal
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    • v.13 no.5
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    • pp.734-742
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    • 2011
  • This study has been undertaken as a basic research for automatic pattern design for baseball uniforms manufactured under custom-MTM system, propose building up of a system whereby various partial patterns are combined under an automatic design system and develop a multi-combination type pattern searching algorithm which allows development of a various designs. As a result of this, type classification based on pattern design elements includes side, open, collar, facing and panel type. Design have been divided into coarse classification ranging from level 1 to 7 according to pattern design elements, based on a design distribution chart. Out of 7 such levels, 3 major types determining design which are, more specifically, level 1 sleeve type, level 2 open type and level 3 collar type, have been taken and combined to determine a total of 12 types to be used for design classification codes. Respective name of style and patterns have been coded using alphabet and numerals. Totally, pattern searching algorithm of multi-combination type has been developed whereby combination of patterns belonging to a specific style can be retrieved automatically once that style name is designated on the automatic pattern design system.

Design of Manufacturing Cell based on Genetic Algorithm (유전 알고리즘에 기초한 제조셀의 설계)

  • 조규갑;이병욱
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.12
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    • pp.72-80
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    • 1998
  • In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

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