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首页> 外文期刊>Journal of ambient intelligence and humanized computing >A particle swarm optimization algorithm for multi-row facility layout problem in semiconductor fabrication
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A particle swarm optimization algorithm for multi-row facility layout problem in semiconductor fabrication

机译:半导体制造中多行设施布局问题的粒子群优化算法

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摘要

Semiconductor chips are the most basic components of smart wearable device and other AI devices. The problem of facility layout in semiconductor fabrication is considered very important, for it will affect the cost saving and performance improvement of the key chips implanted in artificial intelligence production such as intelligent wearable devices. Facility layout problem in semiconductor fabrication is to determine the optimal placement of facilities in a multi-row particular area. In this study, we propose a mathematical model to solve multi-row facility layout problem regarded as a predefined system of discrete points to place the processing modules at different locations in semiconductor fabrication plants (i.e., semiconductor fabrication). Considering the large amounts of computation required we use particle swarm optimization (PSO) algorithm to solve the multi-row facility layout problem by minimizing the total transportation distance between the modules. The results confirm that the PSO algorithm is an effective and practical approach for solving the multi-row facility layout problem within a shorter period. The effect of the number of particles on the efficiency of the PSO algorithm is also discussed in this paper.
机译:半导体芯片是智能可穿戴设备和其他AI设备最基本的组件。半导体制造中的设施布局问题被认为是非常重要的,因为它将影响植入人工智能生产中的钥匙芯片的成本节约和性能改进,例如智能可穿戴设备。半导体制造中的设施布局问题是确定多排特定区域中设施的最佳放置。在这项研究中,我们提出了一种数学模型来解决被认为作为预定义的离散点系统的多行设施布局问题,以将处理模块放置在半导体制造设备(即,半导体制造)中的不同位置。考虑到所需的大量计算,我们使用粒子群优化(PSO)算法通过最小化模块之间的总传输距离来解决多行设施布局问题。结果证实,PSO算法是一种有效实用的方法,用于在较短时段内解决多行设施布局问题。本文还讨论了粒子对PSO算法效率的影响。

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