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    Multiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm

    Source: Journal of Engineering for Gas Turbines and Power:;2001:;volume( 123 ):;issue: 001::page 78
    Author:
    B.-K. Choi
    ,
    B.-S. Yang
    DOI: 10.1115/1.1338952
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, the combined optimization algorithm (immune-genetic algorithm) is proposed for multioptimization problems by introducing the capability of the immune system to the genetic algorithm. The optimizing ability of the proposed combined algorithm is identified by comparing the result of optimization with sharing genetic algorithm for the two-dimensional multipeak function. Also the combined algorithm is applied to minimize the total weight of the shaft and the transmitted forces at the bearings. The results show that the combined algorithm can reduce both the weights of the shaft and the transmitted forces at the bearing with dynamic constraints.
    keyword(s): Algorithms , Bearings , Rotors , Design , Optimization AND Genetic algorithms ,
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      Multiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/125240
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorB.-K. Choi
    contributor authorB.-S. Yang
    date accessioned2017-05-09T00:04:55Z
    date available2017-05-09T00:04:55Z
    date copyrightJanuary, 2001
    date issued2001
    identifier issn1528-8919
    identifier otherJETPEZ-26802#78_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/125240
    description abstractIn this paper, the combined optimization algorithm (immune-genetic algorithm) is proposed for multioptimization problems by introducing the capability of the immune system to the genetic algorithm. The optimizing ability of the proposed combined algorithm is identified by comparing the result of optimization with sharing genetic algorithm for the two-dimensional multipeak function. Also the combined algorithm is applied to minimize the total weight of the shaft and the transmitted forces at the bearings. The results show that the combined algorithm can reduce both the weights of the shaft and the transmitted forces at the bearing with dynamic constraints.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMultiobjective Optimum Design of Rotor-Bearing Systems With Dynamic Constraints Using Immune-Genetic Algorithm
    typeJournal Paper
    journal volume123
    journal issue1
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.1338952
    journal fristpage78
    journal lastpage81
    identifier eissn0742-4795
    keywordsAlgorithms
    keywordsBearings
    keywordsRotors
    keywordsDesign
    keywordsOptimization AND Genetic algorithms
    treeJournal of Engineering for Gas Turbines and Power:;2001:;volume( 123 ):;issue: 001
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian