| The continuous development of the global economy, and improve the living standard of the people all over the world, rising consumer purchasing power and the increasing demand for products, makes the car industry constantly get sustained growth opportunities. Different customers have different requirements for the product characteristics; this requires that the manufacturer must have the ability to produce personalized, diversified products. Indirectly contributed to the widespread use of mixed assembly line in manufacturing enterprises, however, the mixed model assembly lines because of its simultaneous assembly structure and process conditions similar to many types of products, makes its complexity is much higher than a single type of product assembly line. However, as consumer demand for automobile products sustainable growth, lead to car companies receiving orders than the assembly of products in certain production cycle, it urged each car companies must increase its production capacity, in order to meet the diversity of needs of consumers in a certain period of time; otherwise it may lead to the loss of customers. How in the existing production conditions, mixed assembly line corresponding to improve and enhance its ability to produce products has become key issues to consider various enterprises.Based on previous research on the mixed assembly line, combined with current problems facing the auto industry enterprises assembly line. Put forward to optimize a mixed assembly line production rhythm, indirect and improve their ability to produce products; in order to stand out in a competitive environment among the various car companies, improve the competitiveness of its industry, optimization the mixed flow assembly line assembly workers on an assembly line manufacturing cost, reduce automobile part of the product cost. While the workload between the various workstations on an assembly line for analysis, makes workload balancing between various workstations, increasing employees’ sense of fairness, improve fluency mixed assembly line, increase the assembly workers in the assembly quality of multi-objective optimization research, and to establish the corresponding mathematical models.Methods for solving the mixed flow assembly line balancing problem of uncertainty, this article selects the genetic algorithm as a way to solve. Although aspects of this type of genetic algorithm in solving combinatorial optimization problems have a strong advantage, but its slow convergence speed and is easy to fall into local optimal solution of the defect, making the request was mixed assembly line balancing problemof optimal or near-optimal solutions must make appropriate improvements for the shortcomings of genetic algorithm, to improve the performance of the algorithm. In this paper, based on the disadvantages of genetic algorithm and the characteristics of mixed flow assembly line, genetic algorithm to generate the initial population, visualization operation of the algorithm, the way and the probability of crossover and mutation operation settings to improve, and put forward the population expansion mechanism, in order to improve the global search ability of the algorithm. Using the assembly line balancing classic problem to verify this improved algorithm, the results show that the improved algorithm has significantly improved in terms of solution quality and computational efficiency.Finally, through the study of actual cases of auto companies, the results show that multi-objective optimization model proposed balancing the overall energy balance of the mixed model assembly lines, and improved genetic algorithm in solving practical problems can achieve good results, optimization of the issues raised with good performance. |
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