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基于改進(jìn)SA算法在智能制造生產(chǎn)調動(dòng)模型研究
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Application of Improved SA Algorithm for Scheduling Optimization of Industrial Automation Tasks in Intelligent Manufacturing
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    摘要:

    智能制造生產(chǎn)調動(dòng)是一個(gè)復雜的多目標優(yōu)化問(wèn)題,傳統的生產(chǎn)調動(dòng)方法多采用啟發(fā)式方法,在面對復雜的制造環(huán)境,傳統方法可能會(huì )出現早熟收斂或搜索精度下降的問(wèn)題;因此為了解決這些問(wèn)題,研究構建了基于改進(jìn)SA算法的智能制造生產(chǎn)調動(dòng)模型;首先對SA算法進(jìn)行了優(yōu)化,其次利用優(yōu)化后的算法構建了生產(chǎn)調動(dòng)模型,最后通過(guò)仿真實(shí)驗去驗證模式算法的性能。實(shí)驗結果表明,在數據集中,真實(shí)值、模型方法和傳統方法的平均完成時(shí)間分別為85.33min、89.92min和93.81min,其中模型方法與真實(shí)值的差距僅為4.59min。這說(shuō)明模型方法可以用于解決現有生產(chǎn)模式存在拖期的情況,及時(shí)完成生產(chǎn)任務(wù)。模型算法能夠為智能制造生產(chǎn)調動(dòng)提供新的思路。

    Abstract:

    Smart manufacturing production mobilization is a complex multi-objective optimization problem. Traditional production mobilization methods mostly use heuristics, and in the face of complex manufacturing environments, traditional methods may have problems of premature convergence or reduced search accuracy; therefore, in order to solve these problems, the study constructs a smart manufacturing production mobilization model based on the improved SA algorithm; firstly, the SA algorithm is optimized, and secondly, the optimized algorithm is used to construct a production mobilization model. The SA algorithm is optimized, the optimized algorithm is used to construct the production mobilization model, and finally the performance of the model algorithm is verified through simulation experiments. The experimental results show that the average completion time of real value, model method and traditional method are 85.33 min, 89.92 min and 93.81 min respectively in the dataset, and the difference between model method and real value is only 4.59 min. This indicates that the model method can be used to solve the situation of delay in the existing production model and complete the production tasks in time. The model algorithm can provide new ideas for smart manufacturing production mobilization.

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余娜,何國榮,李培東,馬馳.基于改進(jìn)SA算法在智能制造生產(chǎn)調動(dòng)模型研究計算機測量與控制[J].,2023,31(11):293-298.

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歷史
  • 收稿日期:2023-05-22
  • 最后修改日期:2023-05-30
  • 錄用日期:2023-05-30
  • 在線(xiàn)發(fā)布日期: 2023-11-23
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