基于混合遺傳算法的強(qiáng)約束混裝平衡問(wèn)題研究
[Abstract]:The standardization of commodities makes price competition more and more intense, and diversified product demand brings unprecedented challenges to manufacturing organizations. Between the two poles of standardization and diversification, manufacturing enterprises are increasingly using mixed-flow assembly lines to satisfy their customers with customized products and services, without changing or less changing existing production equipment, through the optimization of assembly lines, The manufacturing cost and response speed of mass production are realized by multi-variety assembly. The diversification of automotive product demand has prompted more and more automobile manufacturers to use multi-variety hybrid assembly as an effective means to enhance their competitiveness. Therefore, the balance of hybrid assembly line has become the most important problem in the development of manufacturing industry. In this paper, the scheduling of strongly constrained hybrid assembly line balancing problem is studied. According to the characteristics of strong constraint relation, this paper combines the traditional genetic algorithm and heuristic factor to study the problem. The characteristics of the hybrid assembly line balance problem and the strong constraint relation and the influence of the strong constraint relation on the hybrid assembly line balance are analyzed. The common strong constraint problems in actual production are integrated with the common hybrid assembly line balance problems. To provide the theoretical basis for the actual production and manufacture. Aiming at the complex problem of hybrid assembly line balance with strong constraints, the mathematical model is constructed, and the traditional genetic algorithm is improved from three aspects: 1, and the strong constraint relation is added to the traditional experimental data. In this paper, a new joint priority relation graph is established, and the hybrid assembly line balance problem is transformed into a simple one. The modeling of these hybrid assembly line balancing problems provides theoretical guidance for the actual manufacturing industry. Methods and tools. 2. Three new heuristic factors are introduced in the process of population initialization: the maximum operating time. The maximum number of direct follow-up operations and the maximum number of updatable operations. 3, considering the strong constraint relationship, this paper uses logical strings in the process of crossover and mutation to improve the feasibility of the solution and provide reference value for practical work. In this paper, the hybrid genetic algorithm is used to analyze the proposed hybrid assembly line balance problem with strong constraints, and nine typical cases are used to solve the proposed mathematical model. The improved initialization method improves the feasibility of the initial solution. The optimal solution / optimal solution can be obtained in a short time. The results show that the hybrid genetic algorithm is effective in solving the problem of strongly constrained hybrid assembly line balance.
【學(xué)位授予單位】:武漢科技大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:TH186;TP18
【共引文獻(xiàn)】
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