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    Discrete Optimum Design for Truss Structures by Subset Simulation Algorithm

    Source: Journal of Aerospace Engineering:;2015:;Volume ( 028 ):;issue: 004
    Author:
    Hong-Shuang Li
    ,
    Yuan-Zhuo Ma
    DOI: 10.1061/(ASCE)AS.1943-5525.0000411
    Publisher: American Society of Civil Engineers
    Abstract: This article deals with the design optimization of truss structures with discrete design variables, which remains quite a challenging task in structural design. A new discrete search strategy based on the recently developed subset simulation optimization algorithm is proposed in detail for this type of structural optimization. The discrete design variables are transformed into standard normal variable space to implement the sampling procedure in subset simulation optimization, while the optimization is processed in the discrete design space in the mean time. The performance of the proposed method is illustrated by four representative benchmark optimization problems. Comparisons are made with other well known stochastic optimization algorithms. It is found that the proposed method can produce optimum designs as good as or better than those of other stochastic optimization algorithms.
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      Discrete Optimum Design for Truss Structures by Subset Simulation Algorithm

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    http://yetl.yabesh.ir/yetl1/handle/yetl/81922
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    contributor authorHong-Shuang Li
    contributor authorYuan-Zhuo Ma
    date accessioned2017-05-08T22:31:08Z
    date available2017-05-08T22:31:08Z
    date copyrightJuly 2015
    date issued2015
    identifier other48040055.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/81922
    description abstractThis article deals with the design optimization of truss structures with discrete design variables, which remains quite a challenging task in structural design. A new discrete search strategy based on the recently developed subset simulation optimization algorithm is proposed in detail for this type of structural optimization. The discrete design variables are transformed into standard normal variable space to implement the sampling procedure in subset simulation optimization, while the optimization is processed in the discrete design space in the mean time. The performance of the proposed method is illustrated by four representative benchmark optimization problems. Comparisons are made with other well known stochastic optimization algorithms. It is found that the proposed method can produce optimum designs as good as or better than those of other stochastic optimization algorithms.
    publisherAmerican Society of Civil Engineers
    titleDiscrete Optimum Design for Truss Structures by Subset Simulation Algorithm
    typeJournal Paper
    journal volume28
    journal issue4
    journal titleJournal of Aerospace Engineering
    identifier doi10.1061/(ASCE)AS.1943-5525.0000411
    treeJournal of Aerospace Engineering:;2015:;Volume ( 028 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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