New Matrix Methodology for Algorithmic Transparency in Assembly Line Balancing Using a Genetic Algorithm

IF 3.7 4区管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Perspectives Pub Date : 2022-01-01 DOI:10.1016/j.orp.2022.100223

Juan Ignacio Anel , Pau Català , Moisès Serra , Bruno Domenech

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引用次数: 2

Abstract

This article focuses on the Mixed-Model Assembly Line Balancing single-target problem of type 2 with single-sided linear assembly line configurations, which is common in the industrial environment of small and medium-sized enterprises (SMEs). The main objective is to achieve Algorithmic Transparency (AT) when using Genetic Algorithms for the resolution of balancing operation times. This is done by means of a new matrix methodology that requires working with product functionalities instead of product references.

The achieved AT makes it easier for process engineers to interpret the obtained solutions using Genetic Algorithms and the factors that influence decisions made by algorithms, thereby helping in the later decision-making process. Additionally, through the proposed new matrix methodology, the computational cost is reduced with respect to the stand-alone use of Genetic Algorithms.

The AT produced using the new matrix methodology is validated through its application in an industry-based paradigmatic example.

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基于遗传算法的装配线平衡算法透明性新矩阵方法

本文主要研究了在中小企业工业环境中常见的具有单面线性装配线配置的2型混合模型装配线平衡单目标问题。主要目标是在使用遗传算法解决平衡操作时间时实现算法透明性(AT)。这是通过一种新的矩阵方法来实现的，这种方法需要处理产品功能而不是产品引用。实现的AT使过程工程师更容易使用遗传算法和影响算法做出决策的因素来解释获得的解决方案，从而有助于后期的决策过程。此外，通过提出新的矩阵方法，相对于单独使用遗传算法，计算成本降低。使用新矩阵方法产生的AT通过其在基于行业的范例中的应用得到验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Perspectives Mathematics-Statistics and Probability

CiteScore

6.40

自引率

0.00%

发文量

审稿时长

27 days