本文選題：人工智能 + 多載量小車(chē)�。� 參考：《吉林大學(xué)學(xué)報(bào)(工學(xué)版)》2016年06期

【摘要】：為了有效地解決車(chē)輛裝配系統(tǒng)中多載量小車(chē)的實(shí)時(shí)調(diào)度問(wèn)題,提出了基于支持向量機(jī)的實(shí)時(shí)調(diào)度方法。首先對(duì)多載量小車(chē)的實(shí)時(shí)調(diào)度問(wèn)題進(jìn)行描述,同時(shí)建立以車(chē)輛裝配線產(chǎn)量和物料搬運(yùn)距離作為評(píng)價(jià)指標(biāo)的目標(biāo)函數(shù)。然后通過(guò)車(chē)輛裝配線的物料搬運(yùn)系統(tǒng)仿真生成樣本離線訓(xùn)練支持向量機(jī)模型,在實(shí)時(shí)階段利用支持向量機(jī)模型實(shí)現(xiàn)多載量小車(chē)"等待"或"搬運(yùn)"的調(diào)度決策。試驗(yàn)結(jié)果表明,本文提出的方法明顯優(yōu)于最小批量法,其運(yùn)行速度快、實(shí)時(shí)調(diào)度效果好,且對(duì)動(dòng)態(tài)環(huán)境變化具有一定的自適應(yīng)性,能夠有效提升多載量小車(chē)的實(shí)時(shí)調(diào)度水平。
[Abstract]:In order to effectively solve the real-time scheduling problem of multi-load vehicles in vehicle assembly system, a real-time scheduling method based on support vector machine (SVM) is proposed. Firstly, the real-time scheduling problem of multi-load vehicles is described, and the objective function of vehicle assembly line production and material handling distance is established. Then the sample off-line training support vector machine model is generated by the material handling system simulation of the vehicle assembly line. The support vector machine model is used to realize the scheduling decision of the multi-load vehicle "waiting" or "moving" in the real time stage. The experimental results show that the proposed method is obviously superior to the minimum batch method, its running speed is fast, the real-time scheduling effect is good, and it has certain adaptability to the dynamic environment change, and it can effectively improve the real-time scheduling level of multi-load vehicles.
【作者單位】： 同濟(jì)大學(xué)機(jī)械與能源工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(71471135;61273035)
【分類號(hào)】：U468.2;TP181

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