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    유전자 알고리즘을 이용한 강 뼈대 구조물의 최적설계 = Optimum Design of Steel Frames Using Genetic Algorithms

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    https://www.riss.kr/link?id=A101121333

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    Genetic Algorithms(GA) together with simulated annealing are often called methods of last resorts since they can be applicable to any kind of problems, particularly those to which no sophisticated procedures are applicable or feasible. The design of structures is primarily the process of selecting a section for each member from those available in the market, resulting in the problem of combinatorial nature. Therefore it is usual for the design space to include astronomical number of designs making the search in the space often impossible. In this work, Genetic Algorithms and some related technique are introduced and applied to the design of steel frameworks. In problems with a small number of design variables, GA found true global optima. GA also found true optima for the continuous variable test problems and proved their applicability to structural optimization. For those problems of real size, however, it appears to be difficult to expect GA to find optimum or even near optimum designs. The use of G bit improvement added to ordinary GA has shown much better results and draws attention for further research.
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    Genetic Algorithms(GA) together with simulated annealing are often called methods of last resorts since they can be applicable to any kind of problems, particularly those to which no sophisticated procedures are applicable or feasible. The design of s...

    Genetic Algorithms(GA) together with simulated annealing are often called methods of last resorts since they can be applicable to any kind of problems, particularly those to which no sophisticated procedures are applicable or feasible. The design of structures is primarily the process of selecting a section for each member from those available in the market, resulting in the problem of combinatorial nature. Therefore it is usual for the design space to include astronomical number of designs making the search in the space often impossible. In this work, Genetic Algorithms and some related technique are introduced and applied to the design of steel frameworks. In problems with a small number of design variables, GA found true global optima. GA also found true optima for the continuous variable test problems and proved their applicability to structural optimization. For those problems of real size, however, it appears to be difficult to expect GA to find optimum or even near optimum designs. The use of G bit improvement added to ordinary GA has shown much better results and draws attention for further research.

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