• Title/Summary/Keyword: 랜덤터부탐색

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Vibration Optimization Design of Ship Structure Using NASTRAN-based R-Tabu Search Method (NASTRAN 기반 R-Tabu 탐색법을 이용한 선박구조물의 진동최적설계)

  • 채상일;송진대;김용한;공영모;최수현;양보석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.672-676
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    • 2003
  • Recently, the importance of ship vibration is emerging due to the large scaling, high speed and lightning of ship. For pleasantness in a cabin, shipbuilders ask for strict vibration criteria and the degree of vibration level at a deckhouse became an important condition for taking order from customers. This study conducted optimum design to attenuate vibration level of a deckhouse to solve above problems. New method was implemented, that is NASTRAN external call type independence optimization method. The merit of this method is global searching after setting various object functions and design variables. The global optimization algorithm used here is R-Tabu search method, which has fast converging time and searching various size domains. By modeling similar type to ship structure, validity of the suggested method was investigated.

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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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Development of NASTRAN-based Optimization Framework for Vibration Optimum Design of Ship Structure. (선박 구조물의 진동 최적설계를 위한 NASTRAN 기반 최적화 프레임웍의 제안)

  • Kong, Y.M.;Choi, S.H.;Chae, S.I.;Song, J.D.;Kim, Y.H.;Yang, B.S.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.15 no.11 s.104
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    • pp.1223-1231
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    • 2005
  • Recently, the issue of ship nitration due to the large scale, high speed and lightweight of ship is emerging. For pleasantness in the cabin, shipbuilders are asked for strict vibration criteria and the degree of nitration level at a deckhouse became an important condition for taking order from customers. This study proposes a new optimization framework that is NASTRAN external call type optimization method (OptShip) and applies to an optimum design to decrease the nitration level of a deckhouse. The merits of this method are capable of using of global searching method and selecting of various objective function and design variables. The global optimization algorithms used here are random tabu search method which has fast converging speed and searches various size domains and genetic algorithm which searches multi-point solutions and has a good search capability in a complex space. By adapting OptShip to full-scale model, the validity of the suggested method was investigated.

Development of an Enhanced Artificial Life Optimization Algorithm and Optimum Design of Short Journal Bearings (향상된 인공생명 최적화 알고리듬의 개발과 소폭 저널 베어링의 최적설계)

  • Yang, Bo-Suk;Song, Jin-Dae
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.6
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    • pp.478-487
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    • 2002
  • This paper presents a hybrid method to compute the solutions of an optimization Problem. The present hybrid algorithm is the synthesis of an artificial life algorithm and the random tabu search method. The artificial life algorithm has the most important feature called emergence. The emergence is the result of dynamic interaction among the individuals consisting of the system and is not found in an individual. The conventional artificial life algorithm for optimization is a stochastic searching algorithm using the feature of artificial life. Emergent colonies appear at the optimum locations in an artificial ecology. And the locations are the optimum solutions. We combined the feature of random-tabu search method with the conventional algorithm. The feature of random-tabu search method is to divide any given region into sub-regions. The enhanced artificial life algorithm (EALA) not only converge faster than the conventional artificial life algorithm, but also gives a more accurate solution. In addition, this algorithm can find all global optimum solutions. The enhanced artificial life algorithm is applied to the optimum design of high-speed, short journal bearings and its usefulness is verified through an optimization problem.