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Simultaneous solving of balancing and sequencing problems with station-dependent assembly times for mixed-model assembly lines

机译:同时根据混合装配流水线的装配时间来解决平衡和排序问题

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In spite of many studies, investigating balancing and sequencing problems in Mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new Mixed-Integer Linear Programming (MILP) model is developed to provide the exact solution of the problem with station-dependent assembly times. Because of NP-hardness, a Simulated Annealing (SA) is applied and compared to the Co-evolutionary Genetic Algorithm (Co-GA) from the literature. To strengthen the search process, two main hypotheses, namely simultaneous search and feasible search, are developed contrasting Co-GA. Various parameters of SA are reviewed to calibrate the algorithm by means of Taguchi design of experiments. Numerical results statistically show the efficiency and effectiveness of the proposed SA in terms of both the quality of solution and the time of achieving the best solution. Finally, the contribution of each hypothesis in this superiority is analyzed.
机译:尽管进行了许多研究,但分别研究了混合模型装配线(MMAL)中的平衡和排序问题,本文旨在同时解决这些问题,以最大程度地减少总的公用工作量。开发了一种新的混合整数线性规划(MILP)模型,以根据工作站的装配时间来提供该问题的精确解决方案。由于NP硬度,应用了模拟退火(SA),并将其与文献中的协同进化遗传算法(Co-GA)进行了比较。为了加强搜索过程,对比Co-GA提出了两个主要假设,即同时搜索和可行搜索。通过Taguchi实验设计,回顾了SA的各种参数以校准算法。数值结果从统计学上显示了所提出的SA的效率和有效性,无论是解决方案的质量还是获得最佳解决方案的时间。最后,分析了每个假设在这种优势中的作用。

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