• Title, Summary, Keyword: Optimization

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Structural Optimization Study about Support Structure of Pressure Container (압력용기 지지구조물의 구조최적화 연구)

  • Kim, Chang-Sik
    • Journal of the Korea Institute of Military Science and Technology
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    • v.8 no.2
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    • pp.22-29
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    • 2005
  • In this study we performed topology optimization and size optimization about support structure of pressure container which is installed in a Common Bed. The optimization study shows that structure weight optimization results can be applied to navy ship. The topology optimization is performed by static load, homogenization and optimality criteria method and size optimization is performed by SOL200 of NASTRAN.

A Hybridization of Adaptive Genetic Algorithm and Particle Swarm Optimization for Numerical Optimization Functions

  • Yun, Young-Su;Gen, Mitsuo
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • pp.463-467
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    • 2008
  • Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

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Visualization Tool Design for Searching Process of Particle Swarm Optimization (Particle Swarm Optimization 탐색과정의 가시화를 위한 툴 설계)

  • 유명련
    • Journal of Korea Multimedia Society
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    • v.6 no.2
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    • pp.332-339
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    • 2003
  • To solve the large scale optimization problem approximately, various approaches have been introduced. Recently the Particle Swarm Optimization has been introduced. The Particle Swarm Optimization simulates the process of birds flocking or fish schooling for food, as with the information of each agent is skated by other agents. The Particle Swarm Optimization technique has been applied to various optimization problems whose variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process of Particle Swarm Optimization algorithm. The proposed tool is effective for understanding the searching process of Particle Swarm Optimization method and educational for students. The computational results can be shown tiny and very helpful for education.

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Structural Analysis and Dynamic Design Optimization of a High Speed Multi-head Router Machine (다두 Router Machine 구조물의 경량 고강성화 최적설계)

  • 최영휴;장성현;하종식;조용주
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • pp.902-907
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    • 2004
  • In this paper, a multi-step optimization using a G.A. (Genetic Algorithm) with variable penalty function is introduced to the structural design optimization of a 5-head route machine. Our design procedure consist of two design optimization stage. The first stage of the design optimization is static design optimization. The following stage is dynamic design optimization stage. In the static optimization stage, the static compliance and weight of the structure are minimized simultaneously under some dimensional constraints and deflection limits. On the other hand, the dynamic compliance and the weight of the machine structure are minimized simultaneously in the dynamic design optimization stage. As the results, dynamic compliance of the 5-head router machine was decreased by about 37% and the weight of the structure was decreased by 4.48% respectively compared with the simplified structure model.

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Study of Hybrid Optimization Technique for Grain Optimum Design

  • Oh, Seok-Hwan;Kim, Yong-Chan;Cha, Seung-Won;Roh, Tae-Seong
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.4
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    • pp.780-787
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    • 2017
  • The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.

A teaching learning based optimization for truss structures with frequency constraints

  • Dede, Tayfun;Togan, Vedat
    • Structural Engineering and Mechanics
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    • v.53 no.4
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    • pp.833-845
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    • 2015
  • Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

Hull Form Optimization using Parametric Modification Functions and Global Optimization (전역 최적화기법과 파라메트릭 변환함수를 이용한 선형 최적화)

  • Kim, Hee-Jung;Chun, Ho-Hwan;An, Nam-Hyun
    • Journal of the Society of Naval Architects of Korea
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    • v.45 no.6
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    • pp.590-600
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    • 2008
  • This paper concerns the development of a designer friendly hull form parameterization and its coupling with advanced global optimization algorithms. As optimization algorithms, we choose the Partial Swarm Optimization(PSO) recently introduced to solve global optimization problems. Most general-purpose optimization softwares used in industrial applications use gradient-based algorithms, mainly due to their convergence properties and computational efficiency when a relatively few number of variables are considered. However, local optimizers have difficulties with local minima and non-connected feasible regions. Because of the increase of computer power and of the development of efficient Global Optimization (GO) methods, in recent years nongradient-based algorithms have attracted much attention. Furthermore, GO methods provide several advantages over local approaches. In the paper, the derivative-based SQP and the GO approach PSO are compared with their relative performances in solving some typical ship design optimization problem focusing on their effectiveness and efficiency.

The Integrated Design Optimization Technique for Spatial Structures

  • Lee, Sang-Jin
    • Architectural research
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    • v.14 no.1
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    • pp.19-26
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    • 2012
  • The technique of integrated design optimization is proposed to design spatial structures. Various element technologies such as topology optimization, layout editing and size optimization processes are used in an integrated manner to improve the performance of spatial structures. In order to demonstrate the present technique, a unit spatial structure is optimized and numerical results are described here.

Hopfield neuron based nonlinear constrained programming to fuzzy structural engineering optimization

  • Shih, C.J.;Chang, C.C.
    • Structural Engineering and Mechanics
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    • v.7 no.5
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    • pp.485-502
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    • 1999
  • Using the continuous Hopfield network model as the basis to solve the general crisp and fuzzy constrained optimization problem is presented and examined. The model lies in its transformation to a parallel algorithm which distributes the work of numerical optimization to several simultaneously computing processors. The method is applied to different structural engineering design problems that demonstrate this usefulness, satisfaction or potential. The computing algorithm has been given and discussed for a designer who can program it without difficulty.