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Evaluation of a proposed optimization method for discrete-event simulation models

机译:离散事件仿真模型的一种优化方法的评估

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Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.
机译:与基于计算机的仿真相结合的优化方法已被广泛用于制造应用中。但是,就当前技术而言,这些方法表现出较低的性能水平,只能一次操作一个决策变量。因此,本文的目的是评估一种基于遗传算法的离散事件仿真模型的优化方法,与市场上的软件包相比,该方法在计算时间上具有更高的效率。应该强调的是,变量的响应质量不会改变。也就是说,所提出的方法将保持解决方案的有效性。因此,这项研究在提议的方法与市场上已经可用并已在学术文献中进行了检验的模拟仪器的方法之间进行了比较。提出结论,证实了所提出的优化方法的效率。

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