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混合離散變量的高維多目標(biāo)灰色穩(wěn)健優(yōu)化設(shè)計(jì)
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    摘要:

    提出了一種基于混合離散變量靈敏度分析的高維多目標(biāo)穩(wěn)健性設(shè)計(jì)方法,建立了基于靈敏度分析產(chǎn)生附加目標(biāo)函數(shù)的2種高維多目標(biāo)穩(wěn)健優(yōu)化設(shè)計(jì)模型,應(yīng)用灰色絕對(duì)關(guān)聯(lián)度求解。該模型與方法能合理地處理優(yōu)化設(shè)計(jì)中混合離散變量的取值問題,引入了混沌移民算子對(duì)基本遺傳算法進(jìn)行了改進(jìn),并開發(fā)了混合離散變量?jī)?yōu)化的灰色復(fù)合遺傳算法程序GSCHGA。工程設(shè)計(jì)實(shí)例表明,該算法對(duì)優(yōu)化設(shè)計(jì)問題無特殊要求,具有較好的普適性,而且程序運(yùn)行可靠,全局收斂能力強(qiáng)。

    Abstract:

    A method for robust design was presented based on sensitivity analysis with hybrid discrete variables, and two multi-objective robust optimization design models were established for robust optimization design based on adjunctive function of sensibility analysis. The models were solved with absolute degree of grey incidences. The models and method could reasonably deal with value adopting problems of hybrid discrete variables in optimization design. A chaos emigration operator was introduced to carry out improvement on the fundamental genetic algorithm, and the grey compound genetic algorithmic program GSCHGA for the multi-objective optimization of hybrid discrete variables was developed. Finally, the engineering design example shows that this algorithm has no special requirements on the characteristics of optimal designing problems, good universal adaptability, reliable operation of program, and strong ability of overall convergence. 

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羅佑新,廖德崗,車曉毅,劉奇元.混合離散變量的高維多目標(biāo)灰色穩(wěn)健優(yōu)化設(shè)計(jì)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(9):129-133.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(9):129-133.

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