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基于差異演化算法的動壓滑動軸承多目標(biāo)優(yōu)化
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高等學(xué)校博士學(xué)科點(diǎn)專項(xiàng)科研基金資助項(xiàng)目(20091415110002);山西省自然科學(xué)基金資助項(xiàng)目（2008011027—1）;山西省研究生教育改革研究項(xiàng)目（20092016）;山西省研究生優(yōu)秀創(chuàng)新項(xiàng)目（20093022）


Multi-objective Optimization of Hydrodynamic Sliding Bearing Based on Differential Evolution Algorithm
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    摘要:

    為研究流體動壓軸承的多目標(biāo)優(yōu)化問題,，提出一種改進(jìn)多目標(biāo)差異演化算法。該算法在選擇差分向量時,，對產(chǎn)生差分向量的兩個個體比較其優(yōu)劣,，用非支配解減去支配解，引導(dǎo)個體向非劣解進(jìn)化,，提高算法的收斂速度,；其次提出了種群修剪策略，消除進(jìn)化后期種群中相同個體引起的種群全局搜索能力下降的缺點(diǎn),，以提升算法的全局尋優(yōu)能力,。通過與其它算法的比較，發(fā)現(xiàn)該算法能有效避免“早熟”收斂,，具有較好的收斂速度和多樣性,。工程實(shí)例求解結(jié)果表明了算法的工程可行性。

    Abstract:

    In order to solve multi-objective optimization problem of the hydrodynamic sliding bearing, a modified multi-objective differential evolution algorithm (MMODE) was proposed. The proposed algorithm provided a modified differential vector selection mechanism to improve the convergence speed and a population pruning strategy to maintain the population diversity. The vector selection mechanism compared two selected individuals and used the non-dominated individual minus the domination individual. Compared with several other evolutionary algorithms, the results showed that the proposed algorithm could overcome the premature convergence efficiently and had better convergence and diversity metrics. The results of engineering example showed the feasibility of the proposed algorithm.

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盧青波,張學(xué)良,溫淑花,蘭國生,劉麗琴.基于差異演化算法的動壓滑動軸承多目標(biāo)優(yōu)化[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(3):230-236,245. Lu Qingbo, Zhang Xueliang, Wen Shuhua, Lan Guosheng, Liu Liqin. Multi-objective Optimization of Hydrodynamic Sliding Bearing Based on Differential Evolution Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(3):230-236,245.

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  • 在線發(fā)布日期: 2013-02-25
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