本文關鍵詞：基于混合遺傳禁忌搜索算法的多目標柔性作業(yè)車間調度問題研究　出處：《重慶大學》2012年碩士論文　論文類型：學位論文

  更多相關文章： 工件目標差異 多目標柔性作業(yè)車間調度 混合遺傳禁忌搜索算法 多目標計算方法 雙資源約束

【摘要】：車間調度是制造型企業(yè)生產管理的核心部分，對企業(yè)的盈利能力有著舉足輕重的作用。歷經(jīng)半個多世紀，針對經(jīng)典作業(yè)車間調度問題的研究已經(jīng)取得了豐富的理論成果，但是所建立的模型還不能很好的反映實際生產，不能很好的指導生產。而在經(jīng)典作業(yè)車間調度問題基礎上發(fā)展來的多目標柔性作業(yè)車間調度問題，能夠綜合考慮企業(yè)內部各部門的決策期望，更好的適應現(xiàn)代生產模式的需求，對其研究有著重要的理論意義和實踐意義。 本文在經(jīng)典作業(yè)車間調度的基礎上，描述了柔性作業(yè)車間調度問題，并對多目標柔性作業(yè)車間調度問題進行了建模，，設計了求解算法，主要內容如下： ①提出了包括最大完工時間、平均流經(jīng)時間、瓶頸機器總負荷、機器總負荷、工件交貨期、工件加工成本、產品質量的多個目標，并引入了基于工件目標不同的多目標優(yōu)化概念，并給出了各目標的計算方法。 ②針對工件目標不同的多目標調度問題提出了一種混合遺傳禁忌搜索算法，并采用了一種基于工序和機器的編碼方式，以及新型的基于工序和機器的交叉方式，建立了調度算法。 ③分析了目前常用的多目標優(yōu)化算法，并選定了一種改進的NSGA-ⅡPareto排序方法。 ④建立了更貼近實際生產的基于工件加工目標不同的多目標柔性作業(yè)車間調度問題模型，并提出了以機床和工人為雙約束，工件交貨期為主要目標，總加工成本、瓶頸機器總負荷、總完工時間、單件工件加工成本、單件工件加工質量、單件工件完工時間為次優(yōu)化目標的調度模型。 ⑤以實際項目為基礎，對上述模型進行了仿真，驗證了模型和算法的有效性。
[Abstract]:Job shop scheduling is the core part of production management in manufacturing enterprises, which plays an important role in the profitability of enterprises and has lasted for more than half a century. The research on the classical job shop scheduling problem has made a lot of theoretical achievements, but the established model can not well reflect the actual production. The multi-objective flexible job shop scheduling problem developed on the basis of the classical job shop scheduling problem can comprehensively consider the decision-making expectations of various departments within the enterprise. It is of great theoretical and practical significance to better adapt to the demand of modern production mode. Based on the classical job shop scheduling, the flexible job shop scheduling problem is described in this paper, and the multi-objective flexible job shop scheduling problem is modeled, and a solution algorithm is designed. The main contents are as follows: The main contents are as follows: (1) multiple objectives including the maximum completion time, the average flow time, the total load of the bottleneck machine, the total load of the machine, the delivery time of the workpiece, the processing cost of the workpiece, and the quality of the product are proposed. The concept of multi-objective optimization based on different object of workpiece is introduced, and the calculation method of each target is given. 2. A hybrid genetic Tabu search algorithm is proposed for multi-objective scheduling problem with different job targets, and a coding method based on process and machine is adopted. And a new scheduling algorithm based on process and machine intersection is established. 3. The commonly used multi-objective optimization algorithm is analyzed, and an improved NSGA- 鈪

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