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

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.

Keywords

• Manufacturing
• Mixed-Model Assembly Line Balancing
• Algorithmic Transparency
• new matrix methodology
• Balanced optimization tool for SME