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Analysis of simulated annealing cooling schemas for design of optimal flexible layout under uncertain dynamic product demand

机译:不确定动态产品需求下最优灵活布局设计模拟退火冷却模式的分析

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Manufacturing facilities are subjected to many uncertainties such as variability in demand, queuing delays, variable task times, rejects and machine breakdown. These volatilities have a large impact on leap time, inventory cost and delivery performance of a manufacturing unit. To operate efficiently the manufacturing facilities should adapt to these variations. The paper explores the way uncertainties are addressed in designing of flexible optimal layout. Such facility layout problem is known as stochastic dynamic facility layout problem (SDFLP). SDFLP is an NP-hard combinatorial optimization problem, which means the time taken to solve increases exponentially with problem size. To solve SDFLP, the paper presents an adaptation of simulated annealing (SA) meta-heuristic. Various SA cooling schemas are discussed, computed and evaluated for generating the optimal flexible layout. An optimal layout is one that minimises the distance travelled by materials taking into account uncertain product demand (material handling cost). A computer-based tool was developed and analysis was conducted on small to large size problem set. The results showed that SA with exponential cooling schedule provides better solution in terms of layout efficiency and gave better solution as compared to literature.
机译:制造设施遭受许多不确定性,如需求变异,排队延迟,可变任务时间,拒绝和机器故障等不可思议。这些波动性对闰时间的影响很大,库存成本和制造单位的交付性能。为了有效地运营,制造设施应适应这些变化。本文探讨了在设计灵活的最佳布局方面解决了不确定性的方式。此类设施布局问题被称为随机动态设施布局问题(SDFLP)。 SDFLP是一个NP - 硬组合优化问题,这意味着解决问题所需的时间随问题大小呈指数级。为了解决SDFLP,本文提出了一种模拟退火(SA)元启发式的改编。讨论,计算和评估各种SA冷却模式以产生最佳的灵活布局。最佳布局是以考虑不确定的产品需求(材料处理成本)的材料最小化由材料行进的距离。开发了一种基于计算机的工具,对大小的大尺寸问题进行了分析。结果表明,与指数冷却时间表的SA在布局效率方面提供更好的解决方案,并与文献相比提供了更好的解决方案。

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