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Intelligent design of a dynamic machine layout in uncertain environment of flexible manufacturing systems

机译:柔性制造系统不确定环境下动态机械布局的智能设计

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摘要

Since Facility Layout Problem (FLP) affects the total manufacturing cost significantly, it can be considered as a critical issue in the early stages of designing Flexible Manufacturing Systems (FMSs), particularly in volatile environments where uncertainty in product demands is inevitable. This paper proposes a new mathematical model by using the Quadratic Assignment Problem formulation for designing an optimal machine layout for each period of a dynamic machine layout problem in FMSs. The product demands are considered as independent normally distributed random variables with known Probability Density Function (PDF), which changes from period to period at random. In this model, the decision maker's defined confidence level is also considered. The confidence level represents the decision maker's attitude about uncertainty in product demands in such a way that it affects the results of the problem significantly. To validate the proposed model, two different size test problems are generated at random. Since the FLP, especially in multiperiod case is a hard Combinatorial Optimization Problem (COP), Simulated Annealing (SA) meta-heuristic resolution approach programmed in Matlab is used to solve the mathematical model in a reasonable computational time. Finally, the computational results are evaluated statistically.
机译:由于工厂布局问题(FLP)会严重影响总制造成本,因此在设计柔性制造系统(FMS)的早期阶段,尤其是在产品需求不确定性不可避免的动荡环境中,可以将其视为关键问题。本文使用二次分配问题公式提出了一个新的数学模型,用于为FMS中的动态机器布局问题的每个阶段设计最佳机器布局。产品需求被认为是具有已知概率密度函数(PDF)的独立正态分布随机变量,其随周期而随机变化。在此模型中,还考虑了决策者定义的置信度。置信度表示决策者对产品需求不确定性的态度,从而极大地影响问题的结果。为了验证所提出的模型,随机产生了两个不同大小的测试问题。由于FLP(尤其是在多周期情况下)是一个困难的组合优化问题(COP),因此,在Matlab中编程的模拟退火(SA)元启发式解析方法用于在合理的计算时间内求解数学模型。最后,对计算结果进行统计评估。

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