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A review of the current applications of genetic algorithms in mixed-model assembly line sequencing

机译:遗传算法在混合模型装配线排序中的当前应用综述

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摘要

A mixed-model assembly line (MMAL) is a type of production line which is capable of producing a variety of different product models simultaneously and continuously. The design and planning of such assembly lines involves several long- and short-term problems. Among these problems, determining the sequence of products to be produced has received considerable attention from the researchers. This problem is known as the Mixed-Model Assembly Line Sequencing Problem (MMALSP). An important issue that complicates the sequencing problem is its combinatorial nature. Typically, an enormous number of possible production sequences exist, even for relatively small problems, so that finding the optimal solution is usually impractical. Due to the complexity of the problem, in recent years, a growing number of researchers have employed genetic algorithms (GAs). This paper reviews the genetic algorithm based MMAL sequencing approaches presented in the literature and provides two hierarchical classification schemes to classify academic efforts according to both specifications of MMALSP and specifications of GA-based approaches. Moreover, future research directions have been identified and are suggested.
机译:混合模型装配线(MMAL)是一种生产线,能够同时连续地生产各种不同的产品模型。这种组装线的设计和规划涉及几个长期和短期问题。在这些问题中,确定要生产的产品的顺序已引起研究人员的极大关注。此问题被称为混合模型装配线排序问题(MMALSP)。使排序问题复杂化的一个重要问题是其组合性质。通常,即使对于相对较小的问题,也存在大量可能的生产顺序,因此,找到最佳解决方案通常是不切实际的。由于问题的复杂性,近年来,越来越多的研究人员采用了遗传算法(GA)。本文回顾了文献中提出的基于遗传算法的MMAL排序方法,并提供了两种分层的分类方案,以根据MMALSP的规范和基于GA的方法的规范对学术成果进行分类。此外,已经确定并提出了未来的研究方向。

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