本文選題：流水線調(diào)度　切入點(diǎn)：細(xì)菌覓食算法　出處：《西南交通大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：進(jìn)入21世紀(jì)以來,市場競爭越來越激烈,人們的需求也越來越多樣化,因此結(jié)合多種方法與技術(shù)而產(chǎn)生的先進(jìn)制造系統(tǒng)已經(jīng)成為現(xiàn)階段企業(yè)共同關(guān)注的一種重要的生產(chǎn)制造模式。生產(chǎn)調(diào)度作為先進(jìn)制造系統(tǒng)中的一個(gè)關(guān)鍵的模塊,是企業(yè)提高生產(chǎn)率、降低生產(chǎn)成本、提高綜合實(shí)力的基礎(chǔ)和關(guān)鍵。流水線調(diào)度問題是生產(chǎn)調(diào)度領(lǐng)域研究得最廣泛的問題之一,相關(guān)資料表明：約有四分之一的生產(chǎn)制造系統(tǒng)或組裝線都可以簡化成流水線模型,具有很強(qiáng)的工業(yè)應(yīng)用背景；再加上該問題的NP-hard性質(zhì),常規(guī)方法難以求解,因此對(duì)該問題的研究也具備理論價(jià)值。 論文首先研究了混合流水線調(diào)度問題,對(duì)其研究背景、分類以及研究方法進(jìn)行了分析,為論文的研究做好理論準(zhǔn)備；然后結(jié)合流水線調(diào)度問題的特點(diǎn)以及細(xì)菌覓食優(yōu)化算法求解組合優(yōu)化問題的優(yōu)勢,提出運(yùn)用一種改進(jìn)的細(xì)菌覓食優(yōu)化算法求解流水線調(diào)度問題。其次在深入研究標(biāo)準(zhǔn)細(xì)菌覓食優(yōu)化算法的基礎(chǔ)上,針對(duì)算法的不足,提出引入交叉優(yōu)化算子、混合復(fù)制策略以及基于健康度和適應(yīng)度共同作用的自適應(yīng)遷徙概率以改進(jìn)算法的策略。最后針對(duì)混合流水線調(diào)度問題中的置換流水線調(diào)度問題和零空閑流水調(diào)度問題,分別從編碼方式、初始化、適應(yīng)度函數(shù)、主要操作算子以及終止條件五個(gè)方面進(jìn)行改進(jìn)細(xì)菌覓食優(yōu)化算法的設(shè)計(jì),并通過Matlab編程實(shí)現(xiàn)算法對(duì)典型流水線調(diào)度問題的求解,以驗(yàn)證算法的有效性；同時(shí)通過標(biāo)準(zhǔn)算法和改進(jìn)算法的對(duì)比體現(xiàn)了改進(jìn)算法的優(yōu)化性能,并對(duì)比了兩種初始化方法對(duì)改進(jìn)算法的影響，以驗(yàn)證算法的初始解魯棒性。結(jié)果表明：在中小規(guī)模的流水線調(diào)度問題中,改進(jìn)細(xì)菌覓食優(yōu)化算法的性能優(yōu)于標(biāo)準(zhǔn)算法,能獲得問題的最優(yōu)解,并且具有良好的初值魯棒性。
[Abstract]:Since the beginning of the 21st century, market competition has become more and more intense, and people's needs have become more and more diversified. Therefore, advanced manufacturing system (AMS) combined with many methods and technologies has become an important mode of production and manufacturing that enterprises are paying close attention to at present. Production scheduling is a key module in AMS. Pipeline scheduling is one of the most widely studied problems in the field of production scheduling. The related data show that about 1/4 manufacturing systems or assembly lines can be simplified into pipeline model, which has a strong industrial application background, and the NP-hard properties of the problem make it difficult to solve the problem by conventional methods. Therefore, the study of this problem also has theoretical value. Firstly, the mixed pipeline scheduling problem is studied, the research background, classification and research methods are analyzed, and the theoretical preparation for the research is made. Then combined with the characteristics of pipeline scheduling problem and the advantages of bacterial foraging optimization algorithm to solve combinatorial optimization problem, An improved bacterial foraging optimization algorithm is proposed to solve the pipeline scheduling problem. Secondly, based on the in-depth study of the standard bacterial foraging optimization algorithm, a crossover optimization operator is proposed to solve the deficiency of the algorithm. Hybrid replication strategy and adaptive migration probability based on health and fitness are used to improve the algorithm. The improved bacterial foraging optimization algorithm is designed from five aspects of coding mode, initialization, fitness function, main operator and termination condition, and the solution of typical pipeline scheduling problem is realized by Matlab programming. In order to verify the effectiveness of the algorithm, the optimization performance of the improved algorithm is reflected by the comparison between the standard algorithm and the improved algorithm, and the influence of the two initialization methods on the improved algorithm is compared. The results show that the performance of the improved bacterial foraging optimization algorithm is better than that of the standard algorithm in the small and medium scale pipeline scheduling problem, and the optimal solution of the problem can be obtained, and it has good initial robustness.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TB497;TP18

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