• Journal of Korean Society of Steel Construction
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• v.18 no.2
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• pp.213-223
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• 2006

Conventional truss optimization approaches, while often sophisticated and computationally intensive, have been applied to simple, minimum weight-cost models. These approaches do not perform well when applied to real-world trusses, which have costmodels that are complex and which often involve multiple objectives. Thus, this paper describes the optimization strategies that a clustering technique, which identifies members that are likely to have the same product type, uses for the optimal design of truss structures with real- world cost functions that consider the costs on the weight of the truss, the number of products in the design, the number of joints in the structures, and the costs required in the site.At first, the clustering technique is applied to identify the members and to generate a proper initial solution. A simple taboo search technique is then used, which attempts to generate the optimal solution by starting with the solution from the previous technique. For example, the proposed approach is a plied to a typical problem and to a problem similar to relative performances. The results show that this algorithm generates not only better-quality solutions but also more efficient ones

• Journal of the Korean Wood Science and Technology
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• v.18 no.4
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• pp.3-8
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• 1990

근년에 전세계에서 목재건조 기술의 주요 관심사는 첫째 건조응력발생과 건조결함 예방이고, 다음은 건조실 제어시스템, 건조스케줄개발, 목재수분이동, 함수율측정, 새로운 건조방법개발, 건조에너지 절약, 경제성분석, 태양열건조, 수학적모델링, 건조전처리, 마이크로웨이브 건조, 건조실 구성과 정비, 건조종기결정, 감압건조, 공정제어와 콘다숀닝, 제습건조, 목재치수 안정 및 고온건조 등의 순위이다. 건조중 발생하는 결함들은 건조경비 증가에 절대적인 영향을 끼칠 수 있다. 예를 들면, 가구공장에 있어서 건조재의 품등 향상에 따른 1%의 수율 증대 효과는 가구 부품 1000 보오드피트당 23$의 생산비를 절감할 수 있고, 활엽수재의 천연건조시 수반되는 건조손상은 생재의 23%를 초과할 수 있다. 본 총설이 각종 문제를 개선하고 건조경비를 절감하는데 기여할 수 있기를 바라며, 또한 단판, 칩 또는 땔감과 같은 비제재품에 관한 건조에 관한것은 제외하였다.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.661-672
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• 2005

For the efficient stochastic optimization of steel structures for which a large number of analyses is required, artificial neural networks,which have emerged as a powerful tool that could have been used to replace time-consuming procedures in many scientific or engineering applications, are applied. They are utilized for the solution of the equilibrium equations resulting from the application of the finite element method in connection with the reanalysis type of problem, for which a large number of finite element analyses are required in this study. As such, the use of artificial neural networks to predict finite element analysis outputs simplifies and facilitates the performance of the stochastic optimal design of structural systems where a trained neural network is used to replace the structural reanalysis phase. Moreover, to improve efficiency of used artificial neural networks, genetic algorithm is utilized. The stochastic optimizer used in this study is an algorithm based on the evolution theory. The efficiency of the proposed procedure is examined in problems with both volume (weight) functions and real-world cost functions