本文選題：冷軋　切入點(diǎn)：合同組批　出處：《控制與決策》2017年01期 　論文類(lèi)型：期刊論文

【摘要】：針對(duì)冷軋企業(yè)大批量生產(chǎn)模式與多品種、小批量的市場(chǎng)需求之間存在的矛盾,建立以合同交貨期差異度、工藝路線(xiàn)差異度和調(diào)整次數(shù)最小化為目標(biāo),同時(shí)滿(mǎn)足批次重量、出(入)口寬度、出(入)口厚度、抗拉強(qiáng)度等工藝約束的冷軋合同組批模型,構(gòu)建了基于改進(jìn)粒子群的模糊聚類(lèi)算法并進(jìn)行求解.利用國(guó)內(nèi)某冷軋企業(yè)實(shí)際生產(chǎn)數(shù)據(jù)對(duì)所提出模型和算法進(jìn)行了驗(yàn)證,結(jié)果表明,所提出的方法優(yōu)于FCM算法,能夠滿(mǎn)足企業(yè)批量計(jì)劃的需求.
[Abstract]:In view of the contradiction between the mass production mode of cold rolling enterprise and the market demand of many varieties and small quantities, the aim is to minimize the difference of contract delivery time, process route and adjustment times, and at the same time to meet the weight of batch. Cold rolling contract group model with outlet width, outlet thickness, tensile strength, etc. The fuzzy clustering algorithm based on improved particle swarm optimization is constructed and solved. The proposed model and algorithm are verified by the actual production data of a cold rolling mill in China. The results show that the proposed method is better than FCM algorithm. Able to meet the needs of enterprise batch planning.
【作者單位】： 安徽工業(yè)大學(xué)管理科學(xué)與工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(71172219,71302056) 安徽省科技廳軟科學(xué)重大項(xiàng)目(1502052006)
【分類(lèi)號(hào)】：TG338;TP18
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本文編號(hào)：1627209