本文關(guān)鍵詞： 生產(chǎn)調(diào)度 模擬退火算法 遺傳算法 遺傳模擬退火算法　出處：《鄭州航空工業(yè)管理學(xué)院》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：生產(chǎn)調(diào)度是企業(yè)生產(chǎn)制造過(guò)程中不可或缺的一部分,對(duì)制造企業(yè)的整體運(yùn)營(yíng)起到至關(guān)重要的作用。隨著網(wǎng)絡(luò)技術(shù)、通信技術(shù)的發(fā)展與廣泛運(yùn)用,世界范圍內(nèi)的交流越來(lái)越頻繁,經(jīng)濟(jì)全球化趨勢(shì)越來(lái)越明顯;同時(shí),社會(huì)物質(zhì)條件的改善導(dǎo)致市場(chǎng)需求的變化,市場(chǎng)漸趨多樣化、定制化。全球化的競(jìng)爭(zhēng)以及市場(chǎng)的變化導(dǎo)致企業(yè)傳統(tǒng)的生產(chǎn)方式很難滿(mǎn)足企業(yè)長(zhǎng)期生存的要求,企業(yè)急需要轉(zhuǎn)變生產(chǎn)方式。小品種、定制化的生產(chǎn)方式漸漸被越來(lái)越多的眾多企業(yè)所采納,這樣的生產(chǎn)方式給車(chē)間調(diào)度提出了更高的要求。如何利用現(xiàn)代化的技術(shù)與方法實(shí)現(xiàn)對(duì)生產(chǎn)調(diào)度的統(tǒng)籌優(yōu)化,準(zhǔn)確快速的實(shí)現(xiàn)調(diào)度安排,快速調(diào)配資源,加快企業(yè)的生產(chǎn)效率已成為眾多制造企業(yè)急需解決的問(wèn)題。本文針對(duì)企業(yè)車(chē)間生產(chǎn)調(diào)度問(wèn)題,研究了企業(yè)車(chē)間生產(chǎn)調(diào)度問(wèn)題的數(shù)學(xué)模型以及模擬退火算法和遺傳算法在車(chē)間調(diào)度中的應(yīng)用。針對(duì)兩種算法的各自特性與優(yōu)缺點(diǎn)提出并設(shè)計(jì)了改進(jìn)遺傳模擬退火算法。并且,文章應(yīng)用典型案例的求解結(jié)果對(duì)比,分析證實(shí)了算法的有效性與良好的性能。最后,通過(guò)應(yīng)用改進(jìn)遺傳模擬退火算法對(duì)實(shí)際案例進(jìn)行求解,進(jìn)一步驗(yàn)證算法的可行性與實(shí)用性。文章對(duì)于遺傳模擬退火算法在生產(chǎn)調(diào)度問(wèn)題中的應(yīng)用與算法的優(yōu)化進(jìn)行了深入的研究,通過(guò)改進(jìn)算法的變異算子、選擇算子提高了算法的優(yōu)化求解性能以及規(guī)避“早熟”問(wèn)題的能力。
[Abstract]:Production scheduling is an indispensable part of the manufacturing process, which plays a vital role in the overall operation of manufacturing enterprises. With the development and wide application of network technology, communication technology. Worldwide exchanges are becoming more and more frequent, and the trend of economic globalization is becoming more and more obvious. At the same time, the improvement of social material conditions leads to the change of market demand and the diversification of market. Customization. The globalization of competition and market changes lead to the traditional mode of production is difficult to meet the long-term survival requirements of enterprises, enterprises urgently need to change production methods. Small varieties. The customized mode of production is gradually adopted by more and more enterprises. This mode of production puts forward higher requirements for job shop scheduling. How to use modern technology and methods to achieve the overall optimization of production scheduling, accurate and rapid implementation of scheduling arrangements, rapid allocation of resources. Speeding up the production efficiency of enterprises has become a problem that many manufacturing enterprises urgently need to solve. The mathematical model of shop shop scheduling problem and the application of simulated annealing algorithm and genetic algorithm in job shop scheduling are studied. The improved genetic simulated annealing is proposed and designed according to the respective characteristics, advantages and disadvantages of the two algorithms. Algorithm. And. In this paper, the results of typical cases are compared, and the effectiveness and good performance of the algorithm are verified. Finally, the improved genetic simulated annealing algorithm is used to solve the actual cases. Further verify the feasibility and practicability of the algorithm. In this paper, the genetic simulated annealing algorithm in production scheduling problems and optimization of the application of in-depth research, by improving the algorithm mutation operator. The selection operator improves the optimization performance of the algorithm and the ability to avoid the precocious problem.
【學(xué)位授予單位】：鄭州航空工業(yè)管理學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP18;TB497

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