• Title/Summary/Keyword: Annealing Algorithm

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Task Sequence Optimization for 6-DOF Manipulator in Press Forming Process (프레스 공정에서 6자유도 로봇의 작업 시퀀스 최적화)

  • Yoon, Hyun Joong;Chung, Seong Youb
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.2
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    • pp.704-710
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    • 2017
  • Our research team is developing a 6-DOF manipulator that is adequate for the narrow workspace of press forming processes. This paper addresses the task sequence optimization methods for the manipulator to minimize the task-finishing time. First, a kinematic model of the manipulator is presented, and the anticipated times for moving among the task locations are computed. Then, a mathematical model of the task sequence optimization problem is presented, followed by a comparison of three meta-heuristic methods to solve the optimization problem: an ant colony system, simulated annealing, and a genetic algorithm. The simulation shows that the genetic algorithm is robust to the parameter settings and has the best performance in both minimizing the task-finishing time and the computing time compared to the other methods. Finally, the algorithms were implemented and validated through a simulation using Mathworks' Matlab and Coppelia Robotics' V-REP (virtual robot experimentation platform).

Design of Adaptive Inverse Control for Center Position Control of Steel-Strip in Continuous Annealing Line (연속소둔로에서 판중심 위치 제어를 위한 적응 역비례 제어기의 설계)

  • Kim, Young-Su;Jo, Sung-Eun;Lee, Young-Kow;Kim, Sang-Woo
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.608-610
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    • 2004
  • In continuous annealing line (CAL), POSCO, the center position control (CPC) is an essential technique that renders the steel-strip to pass at the center of a roll in order to prevent the strip from skewing or breaking. The CPC algorithm currently installed on the steering roll in the heating section of CAL is to control the strip position by using the reverse phase of error from the center position, without considering the dynamics of strip horizontal movement. Such algorithm may, unfortunately, require a manual operation occasionally when the range of strip input becomes wide, causing the dynamics 0 be dominant. Other PID-type control is rarely used in automatic operation because the excess of response may occur when the discontinuous points such as welding joints pass through rolls. In this paper, we identify the CPC system by using off-line data and design a compensator for the excessive dynamics by using the adaptive inverse control. Simulation result depicts the improved reliability of the proposed CPC system.

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SIMULATED ANNEALING FOR LINEAR SCHEDULING PROJECTS WITH MULTIPLE RESOURCE CONSTRAINTS

  • C.I. Yen
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.530-539
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    • 2007
  • Many construction projects such as highways, pipelines, tunnels, and high-rise buildings typically contain repetitive activities. Research has shown that the Critical Path Method (CPM) is not efficient in scheduling linear construction projects that involve repetitive tasks. Linear Scheduling Method (LSM) is one of the techniques that have been developed since 1960s to handle projects with repetitive characteristics. Although LSM has been regarded as a technique that provides significant advantages over CPM in linear construction projects, it has been mainly viewed as a graphical complement to the CPM. Studies of scheduling linear construction projects with resource consideration are rare, especially with multiple resource constraints. The objective of this proposed research is to explore a resource assignment mechanism, which assigns multiple critical resources to all activities to minimize the project duration while satisfying the activities precedence relationship and resource limitations. Resources assigned to an activity are allowed to vary within a range at different stations, which is a combinatorial optimization problem in nature. A heuristic multiple resource allocation algorithm is explored to obtain a feasible initial solution. The Simulated Annealing search algorithm is then utilized to improve the initial solution for obtaining near-optimum solutions. A housing example is studied to demonstrate the resource assignment mechanism.

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Discrete sizing and layout optimization of steel truss-framed structures with Simulated Annealing Algorithm

  • Bresolin, Jessica M.;Pravia, Zacarias M.C.;Kripka, Moacir
    • Steel and Composite Structures
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    • v.44 no.5
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    • pp.603-617
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    • 2022
  • Structural design, in general, is developed through trial and error technique which is guided by standards criteria and based on the intuition and experience of the engineer, a context that leads to structural over-dimensioning, with uneconomic solutions. Aiming to find the optimal design, structural optimization methods have been developed to find a balance between cost, structural safety, and material performance. These methods have become a great opportunity in the steel structural engineering domain since they have as their main purpose is weight minimization, a factor directly correlated to the real cost of the structure. Assuming an objective function of minimum weight with stress and displacement constraints provided by Brazilian standards, the present research proposes the sizing optimization and combined approach of sizing and shape optimization, through a software developed to implement the Simulated Annealing metaheuristic algorithm. Therefore, two steel plane frame layouts, each admitting four typical truss geometries, were proposed in order to expose the difference between the optimal solutions. The assessment of the optimal solutions indicates a notable weight reduction, especially in sizing and shape optimization combination, in which the quantity of design variables is increased along with the search space, improving the efficiency of the optimal solutions achieved.

Development of a Design System for Multi-Stage Gear Driver (1st Report : Proposal Formal Processes for Dimensional Design)

  • Chong, Tae-Hyoun
    • International Journal of Precision Engineering and Manufacturing
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    • v.2 no.2
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    • pp.57-64
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    • 2001
  • In recent years, the concern of designing multi-stage gear drives ha increased with more application of them in high-speed and high-load. Until now, however, the researches on the design of gear drives have been focused on single gear pairs. Thus the design practice for multi-stage gear drives has been depended on experiences and expertise of designers and carried out commonly by trial and error. We propose an automation algorithm for the design of two-and three-strage cylindrical gear drives. The two types of dimensional design processes have been proposed to determine gear dimensions in a formal way. The first design process(Process I) uses to total volume of gears to determine gear ration , and uses K factor , unit load and aspect ration to determine gear dimensions, The second one(Process II) makes use of Niemann's formula and center distance to calculate gear ratio and gear dimensions. Process I and Process II employ material date from AGMA and ISO standards, respectively. The configuration design determines the positions of gears with minimizing the volume of gearbox by using a simulated annealing algorithm. The availability of the design algorithm is validated by the design examples to two-and three=stage gear drives.

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A Study of Formation of Machine Cell-Part Family in FMS using the Simulated Annealing Algorithm (시뮬레이티드 어닐링 알고리즘을 이용한 유연생산시스템의 기계셀-부품군 형성에 관한 연구)

  • Kim, Jin-Yong;Park, Dae-Geuk;Oh, Byeong-Wan;Hong, Sung-Jo;Choi, Jin-Yeong
    • IE interfaces
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    • v.10 no.2
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    • pp.1-13
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    • 1997
  • The problem of the formation of machine-part cells in FMS is a very important issue at the planning and operating stages of FMS. This problem is inherently a combinatorial optimization problem, proven to be NP-complete(or, NP-hard). Among the several kinds of approaches which have been applied to solve the combinatorial optimization problems, the Simulated Annealing(SA) algorithm, a technique of random search type with a flexibility in generating alternatives, is a powerful problem solving tool. In this paper, the SA algorithm is used to solve machine cell-part family formation problems. The primary purpose of the study is to find the near-optimal solution of machine cell-part family formation problem, whare the product volume and number of operations are prespecified, that can minimize the total material handling cost caused by exceptional elements and intercell moves as much as possible. The results show that the SA algorithm is able to find a near-optimal solution for practical problems of the machine cell-part family formation.

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Image Encryption and Decryption Using SA Algorithm and Optical Correlator System (SA 알고리듬과 광 상관 시스템을 이용한 영상 암호화 및 복호화)

  • 김철수;조창섭
    • Journal of Korea Multimedia Society
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    • v.7 no.3
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    • pp.349-356
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    • 2004
  • In this paper, a practical image security system using SA algorithm and 4-f optical correlator system is proposed. The encrypted image and key image with binary phase components are generated using an iterative SA algorithm. a decrypted image is found through the correlation of the encrypted and key images using 4-f optical correlator system. The encrypted and key images are consisted of binary phase components. So, it is easy to implement the optical security system using the proposed technique. And if we fix the encrypted image in the optical security system and change the key images, we get different images, so it is possible to apply to the distinguished authorization system using different key images. Computer simulations show that despite the binary phase components of the two images(encrypted and key image), decrypted images are generated.

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A Clustering Algorithm for Handling Missing Data (손실 데이터를 처리하기 위한 집락분석 알고리즘)

  • Lee, Jong Chan
    • Journal of the Korea Convergence Society
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    • v.8 no.11
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    • pp.103-108
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    • 2017
  • In the ubiquitous environment, there has been a problem of transmitting data from various sensors at a long distance. Especially, in the process of integrating data arriving at different locations, data having different property values of data or having some loss in data had to be processed. This paper present a method to analyze such data. The core of this method is to define an objective function suitable for the problem and to develop an algorithm that can optimize this objective function. The objective function is used by modifying the OCS function. MFA (Mean Field Annealing), which was able to process only binary data, is extended to be applicable to fields with continuous values. It is called CMFA and used as an optimization algorithm.

Efficient Algorithms for Solving Facility Layout Problem Using a New Neighborhood Generation Method Focusing on Adjacent Preference

  • Fukushi, Tatsuya;Yamamoto, Hisashi;Suzuki, Atsushi;Tsujimura, Yasuhiro
    • Industrial Engineering and Management Systems
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    • v.8 no.1
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    • pp.22-28
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    • 2009
  • We consider facility layout problems, where mn facility units are assigned into mn cells. These cells are arranged into a rectangular pattern with m rows and n columns. In order to solve this cell type facility layout problem, many approximation algorithms with improved local search methods were studied because it was quite difficult to find exact optimum of such problem in case of large size problem. In this paper, new algorithms based on Simulated Annealing (SA) method with two neighborhood generation methods are proposed. The new neighborhood generation method adopts the exchanging operation of facility units in accordance with adjacent preference. For evaluating the performance of the neighborhood generation method, three algorithms, previous SA algorithm with random 2-opt neighborhood generation method, the SA-based algorithm with the new neighborhood generation method (SA1) and the SA-based algorithm with probabilistic selection of random 2-opt and the new neighborhood generation method (SA2), are developed and compared by experiment of solving same example problem. In case of numeric examples with problem type 1 (the optimum layout is given), SA1 algorithm could find excellent layout than other algorithms. However, in case of problem type 2 (random-prepared and optimum-unknown problem), SA2 was excellent more than other algorithms.

Constructing relationships in a hierarchical file system

  • Yoon, Young-Woo
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.902-908
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    • 2006
  • We propose a scheme for more efficient navigation in a hierarchical file system. In the proposed scheme, a program running in the background computes the degree of relationship between a current file and others, and builds a list of the most related files. The current relationship metric being used by the program is a linear combination of five parameters: the name, the directory path, the type, the created time, and the last accessed time of a file. A simulated annealing algorithm is used in order to determine the weighting factors of the parameters. A set of experiments were conducted in order to access the effectiveness of the proposed scheme.

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