本文選題：混合流水車間調(diào)度　切入點：分布估計算法　出處：《大連交通大學(xué)》2014年碩士論文

【摘要】：近些年來,隨著社會的逐步發(fā)展,科學(xué)技術(shù)的重要性在社會的生產(chǎn)發(fā)展中日益凸顯。通過利用科學(xué)技術(shù)的進步與發(fā)展來提高生產(chǎn)效率、降低生產(chǎn)成本、提高企業(yè)競爭力越來越受到各領(lǐng)域的重視。所謂車間調(diào)度,就是要分配現(xiàn)有資源來滿足企業(yè)的正常、有序、快速生產(chǎn),也就是說要分配好工件、設(shè)備的加工順序及與時間的關(guān)系,以達到設(shè)備的最大化利用和提高生產(chǎn)效率的目的。因此,深入地研究車間調(diào)度問題有著重要的科研及生產(chǎn)價值。 目前社會處在高速發(fā)展階段,越來越多的車間調(diào)度出現(xiàn)在社會生產(chǎn)中,也隨之出現(xiàn)了很多智能優(yōu)化算法。分布估計算法(Estimation of Distribution Algorithm, EDA)是近年來新興的一種進化算法,它將建立概率模型和采樣引入到進化的過程中,而不是遺傳算法里的變異和交叉操作。分布估計算法是通過概率模型進行的全局搜索優(yōu)化。這樣能夠避免一些傳統(tǒng)優(yōu)化算法的缺陷出現(xiàn)。分布估計算法的優(yōu)化效率,優(yōu)化性能,優(yōu)化效果等方面表現(xiàn)的比其他很多算法更優(yōu)秀,更符合實際需求。 本文分析了置換的流水車間調(diào)度問題和更為復(fù)雜的混合流水車間調(diào)度問題特點、分類等情況,研究了目前出現(xiàn)的一些主要其他算法對于這類問題的求解并分析這些算法求解這類問題的優(yōu)點和不足之處。本文將基于分布估計算法這一基礎(chǔ)算法求解流水車間調(diào)度問題。根據(jù)分析出的其他算法對于求解這類問題的優(yōu)點和不足之處,為了到達發(fā)揚這些優(yōu)勢并避免那些不足處的母體,本文對分布估計算法進行了適當(dāng)?shù)母倪M,改進的分布估計算法有著更高的優(yōu)化效率,更強的優(yōu)化性能,更好更優(yōu)秀的優(yōu)化效果。 最后本文通過車間調(diào)度中經(jīng)典的Rec類問題數(shù)據(jù)和具體車間調(diào)度實例對改進的分布估計算法進行了測試和性能的驗證試驗,并將測試結(jié)果很好很直觀的與其他算法進行了比較,結(jié)果數(shù)據(jù)都顯示出了改進的分布估計算法的優(yōu)良的性能。然后通過模擬調(diào)度系統(tǒng)的實現(xiàn),更進一步驗證了改進的分布估計算法的有效性和優(yōu)越性。
[Abstract]:In recent years, with the gradual development of society, the importance of science and technology has become increasingly prominent in the development of social production.By using the progress and development of science and technology to improve production efficiency, reduce production costs and improve the competitiveness of enterprises, more and more attention has been paid to various fields.The so-called workshop scheduling is to allocate existing resources to meet the normal, orderly and rapid production of enterprises, that is to say, to allocate the processing order of jobs and equipment and their relationship with time.In order to maximize the use of equipment and improve production efficiency.Therefore, the in-depth study of job shop scheduling has important scientific research and production value.At present, the society is in the high speed development stage, more and more job shop scheduling appears in the social production, also appeared many intelligent optimization algorithms.Estimation of Distribution algorithm (EDAA) is a new evolutionary algorithm in recent years. It introduces probabilistic model and sampling into evolutionary process, rather than mutation and crossover operation in genetic algorithm.Distribution estimation algorithm is a global search optimization based on probabilistic model.In this way, the defects of some traditional optimization algorithms can be avoided.The optimization efficiency, optimization performance and optimization effect of the distributed estimation algorithm are better than many other algorithms and meet the actual needs.In this paper, we analyze the characteristics and classification of income job shop scheduling problem and the more complex hybrid income job shop scheduling problem.The advantages and disadvantages of some other algorithms for solving this kind of problems are studied and the advantages and disadvantages of these algorithms are analyzed.In this paper, the basic algorithm based on the distribution estimation algorithm is used to solve the income job shop scheduling problem.According to the advantages and disadvantages of other algorithms for solving this kind of problems, in order to develop these advantages and avoid the disadvantages of the matrix, this paper makes a proper improvement on the distribution estimation algorithm.The improved distribution estimation algorithm has higher optimization efficiency, better optimization performance and better optimization effect.Finally, this paper tests and verifies the performance of the improved distributed estimation algorithm by using the classic Rec class problem data and specific job shop scheduling examples, and compares the test results with other algorithms directly.The results show that the improved distribution estimation algorithm has good performance.Then, the effectiveness and superiority of the improved distribution estimation algorithm are further verified by the implementation of the simulation scheduling system.
【學(xué)位授予單位】：大連交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TB497

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