本文選題：車間作業(yè)調(diào)度　切入點：改進(jìn)遺傳算法　出處：《青島理工大學(xué)》2011年碩士論文　論文類型：學(xué)位論文

【摘要】：車間作業(yè)調(diào)度問題（Job-shop Scheduling Problem，簡稱JSP）是生產(chǎn)管理的關(guān)鍵內(nèi)容之一，好的求解方法不僅可以提高生產(chǎn)效率、降低生產(chǎn)成本，而且還可以加快企業(yè)對市場的響應(yīng)速度以提高企業(yè)的經(jīng)濟(jì)效益和市場競爭力。由于車間作業(yè)調(diào)度問題是典型的NP-hard問題，傳統(tǒng)的優(yōu)化算法很難求得其最優(yōu)解，所以本文在前人研究的基礎(chǔ)上，采用了目前應(yīng)用最廣泛的遺傳算法作為求解方法，并對傳統(tǒng)的遺傳算法進(jìn)行了改進(jìn)，提高了算法優(yōu)化性能。 設(shè)計了基于優(yōu)先權(quán)矩陣的編碼方法，并建立了以最大完工時間為目標(biāo)的車間作業(yè)調(diào)度優(yōu)化數(shù)學(xué)模型，根據(jù)優(yōu)先權(quán)矩陣編碼方法，設(shè)計了相應(yīng)的交叉和變異算子，實例計算表明該改進(jìn)遺傳算法可以提高對車間作業(yè)調(diào)度問題的尋優(yōu)能力和求解效率。 建立了柔性車間作業(yè)調(diào)度模型，設(shè)計了基于雙層編碼的遺傳算法對其進(jìn)行求解，并以優(yōu)先權(quán)編碼為基礎(chǔ)設(shè)計了相應(yīng)的雙層編碼方法、解碼算子、交叉算子和變異算子，，針對不同的優(yōu)化目標(biāo)對計算實例進(jìn)行了優(yōu)化。 以最大完工時間、機(jī)床最大負(fù)荷、機(jī)床總負(fù)荷與交貨期為目標(biāo)，建立了多目標(biāo)柔性車間作業(yè)調(diào)度問題的數(shù)學(xué)模型。根據(jù)其特點設(shè)計了分層Pareto非劣前沿分級方法，提高了優(yōu)化效率。 分析了調(diào)度問題中的時間因素，將工件運輸時間作為獨立一部分進(jìn)行計算，使得調(diào)度模型更加貼近生產(chǎn)實際。 在相應(yīng)理論研究的基礎(chǔ)上，采用VC++語言編制完成了車間作業(yè)調(diào)度優(yōu)化設(shè)計軟件，優(yōu)化實例表明了算法的有效性。
[Abstract]:Job shop scheduling problem Job-shop Scheduling problem (JSP) is one of the key contents of production management. A good solution method can not only improve production efficiency, but also reduce production cost. Moreover, it can speed up the response of enterprises to the market to improve their economic efficiency and market competitiveness. Because the job-shop scheduling problem is a typical NP-hard problem, it is difficult for the traditional optimization algorithm to find its optimal solution. Therefore, based on the previous research, this paper adopts the most widely used genetic algorithm as the solution method, and improves the traditional genetic algorithm to improve the optimization performance of the algorithm. The coding method based on priority matrix is designed, and the mathematical model of job shop scheduling optimization with maximum completion time is established. According to the coding method of priority matrix, the corresponding crossover and mutation operators are designed. The example shows that the improved genetic algorithm can improve the optimization ability and efficiency of the job shop scheduling problem. The flexible job shop scheduling model is established, and the genetic algorithm based on two-layer coding is designed to solve it. Based on priority coding, the corresponding double-layer coding method, decoding operator, crossover operator and mutation operator are designed. The calculation examples are optimized for different optimization objectives. Aiming at the maximum completion time, the maximum load of machine tool, the total load of machine tool and the due date, the mathematical model of multi-objective flexible job shop scheduling problem is established. According to its characteristics, a hierarchical Pareto non-inferior frontier classification method is designed. The optimization efficiency is improved. The time factor in the scheduling problem is analyzed and the workpiece transportation time is calculated as an independent part to make the scheduling model more close to the production practice. On the basis of the corresponding theoretical research, the optimization design software of job shop scheduling is developed by using VC language. The optimization example shows the effectiveness of the algorithm.
【學(xué)位授予單位】：青島理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2011
【分類號】：TH186;TP18

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