Simulation of manufacturing operations: optimization of buffer sizes in assembly systems using intelligent techniques
Simulation of manufacturing operations: optimization of buffer sizes in assembly systems using intelligent techniques
复制标题
制造操作模拟：使用智能技术优化装配系统中的缓冲区大小
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
A. Bulgak
中科院分区：
文献类型：
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作者：
Fulya Altiparmak;B. Dengiz;A. Bulgak
当所研究的系统很复杂时，这些系统的解析解就变得不可能了。由于系统的复杂随机特性，仿真可以作为预测现有系统性能的分析工具，也可以作为在不同环境下测试新系统的设计工具。然而，对于大多数实际感兴趣的问题，模拟是非常耗时的。因此，对系统性能进行任何参数研究都是不切实际的，特别是对于参数空间较大的系统。克服这一限制的一种方法是开发一个更简单的模型来解释系统的输入和输出之间的关系。模拟元模型越来越多地与原始模拟结合使用，以改进对决策过程的分析和理解。建立了异步装配系统仿真模型的人工神经网络(ANN)元模型，并将ANN元模型与模拟退火法(SA)相结合对系统中的缓冲区大小进行优化。
When the systems under investigation are complex, the analytical solutions to these systems become impossible. Because of the complex stochastic characteristics of the systems, simulation can be used as an analysis tool to predict the performance of an existing system or a design tool to test new systems under varying circumstances. However, simulation is extremely time consuming for most problems of practical interest. As a result, it is impractical to perform any parametric study of system performance, especially for systems with a large parameter space. One approach to overcome this limitation is to develop a simpler model to explain the relationship between the inputs and outputs of the system. Simulation metamodels are increasingly being used in conjunction with the original simulation, to improve the analysis and understanding of decision-making processes. In this study, artificial neural networks (ANN) metamodel is developed for simulation model of an asynchronous assembly system and ANN metamodel together with simulated annealing (SA) is used to optimize the buffer sizes in the system.