本文關鍵詞： 柔性流水車間調(diào)度 批處理特征 總加權完成時間 自適應遺傳算法 自適應調(diào)節(jié) 煉鋼-連鑄-熱軋 鋼鐵生產(chǎn)　出處：《鄭州大學》2017年碩士論文　論文類型：學位論文

【摘要】：在鋼鐵行業(yè),煉鋼、連鑄、熱軋作為煉鋼的主要工序,生產(chǎn)出的鐵道鋼材、鋼板樁及大中小型鋼等極大地促進了國民經(jīng)濟的發(fā)展,在整個流程中起著重要作用。從煉鋼-連鑄-熱軋生產(chǎn)過程中提煉出的多階段柔性流水車間調(diào)度問題(Flexible Flowshop Scheduling Problem,FFSP),不僅需要滿足鋼鐵生產(chǎn)的一系列約束條件,而且具有批處理的特征。帶有批處理特征的多階段FFSP是經(jīng)典FFSP的延伸,要求同一批次內(nèi)所有工件都要按照已知的優(yōu)先級順序,在同一臺機器上進行無間斷地加工。本文結合實際情況,對FFSP進行相關理論分析,并對國內(nèi)外相關領域的研究進行學習。通過分析,對FFSP的應用現(xiàn)狀進行總結,確定本文的研究問題。從鋼鐵生產(chǎn)的煉鋼-連鑄-熱軋工藝中提煉出含有串行批處理特征的多階段FFSP,綜合考慮實際生產(chǎn)中的各種約束條件,以總加權完成時間最小化為目標建立數(shù)學模型。首先對連鑄-熱軋結構進行分析,可以將其看做為第一階段有多臺串行批處理機而其它階段為離散機的FFSP,考慮工件在各加工階段間的運輸時間,利用本文提出的改進的自適應遺傳算法進行優(yōu)化求解。其次將連鑄-熱軋工藝向上游延伸,剖析煉鋼-連鑄-熱軋生產(chǎn)過程的特點,歸納出中間階段有多臺批處理機,其它階段為離散機的多階段柔性流水車間調(diào)度問題。結合工件動態(tài)到達,各加工階段間的運輸時間以及機器的調(diào)整時間等生產(chǎn)特征,對問題進行數(shù)學描述并求解。針對不同的問題,本文分別對多達240個工件和150個工件的不同規(guī)模的大量隨機數(shù)據(jù)進行仿真測試。并將拉格朗日松弛算法以及傳統(tǒng)的遺傳算法與本文所提出的改進的自適應遺傳算法進行比較,結果表明,與常規(guī)遺傳算法相比,所提出的自適應遺傳算法能在較短的計算時間內(nèi)得到更好的解;與拉格朗日松弛算法對比,當所要求解的問題為中大規(guī)模時,所提算法在解的質(zhì)量方面優(yōu)勢較為明顯。
[Abstract]:In the steel industry, steelmaking, continuous casting, hot rolling as the main process of steelmaking, railway steel production of steel sheet pile and the small and medium-sized steel has greatly promoted the development of the national economy, plays an important role in the whole process. Multi stage flexible flow shop scheduling problem derived from steelmaking continuous casting hot rolling production process (the Flexible Flowshop Scheduling Problem, FFSP), not only need to meet a series of constraints of steel production, but also has the characteristics of batch processing. Multi stage FFSP with batch characteristics is the extension of the classic FFSP requirements within the same batch of all jobs according to the known priority of uninterrupted processing in the same on a single machine. Combining with the actual situation, analyzes the related theories of FFSP, and the domestic and foreign research related fields of study. Through the analysis, the application of FFSP are summarized, indeed Study on the problem in this paper. From the production of iron and steel steelmaking continuous casting hot rolling process to extract containing multi stage FFSP serial batch processing feature, considering various constraints in actual production, to minimize the total weighted completion time to establish the mathematical model for the goal. Firstly, continuous casting and hot rolling structure analysis, can be seen as for the first stage of a serial batching machine and other stage for discrete machine FFSP, considering the workpiece in each processing stage of the transport time, optimize the use of the improved adaptive genetic algorithm is proposed in this paper. Secondly, continuous casting and hot rolling process to extend upstream, analyze the characteristics of steelmaking continuous casting hot rolling production process, summed up the intermediate stage of a plurality of batch processing machines, other stages of multistage flexible flow shop scheduling problem of discrete machine. Combined with dynamic job arrivals, each processing stage between transportation And adjust the time machine production characteristics, mathematical description and solving the problem. According to different problems, this paper respectively up to 240 pieces and 150 workpieces of different sizes in a random data simulation test. And the comparison of improved adaptive genetic algorithm Lagrange relaxation algorithm and traditional genetic algorithm and the the results show that compared with the conventional genetic algorithm, the proposed adaptive genetic algorithm can get a better solution within a short time; compared with the Lagrange relaxation algorithm to solve the problem when in large scale, the proposed algorithm is more obvious in the solution quality advantages.

【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TF758

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本文編號：1535029