2016/12/16 by Menouar Boulif, Menouar, Boulif
Engineering · #90C59 #Advanced Manufacturing and Logistics Optimization #Assembly Line Balancing Optimization #Discrete Mathematics (cs.DM) #FOS: Computer and information sciences #Flexible and Reconfigurable Manufacturing Systems #Neural and Evolutionary Computing (cs.NE)
paper · pdf · doi:10.48550/arxiv.1612.05536
openalex publication_date 2016/12/16 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
Cell formation is a critical step in the design of cellular manufacturing systems. Recently, it was tackled using a cut-based-graph-partitioning model. This model meets real-life production systems requirements as it uses the actual amount of product flows, it looks for the suitable number of cells, and it takes into account the natural constraints such as operation sequences, maximum cell size, cohabitation and non-cohabitation constraints. Based on this model, we propose an original encoding representation to solve the problem by using a genetic algorithm. We discuss the performance of this new GA in comparison to some approaches taken from the literature on a set of medium sized instances. Given the results we obtained, it is reasonable to assume that the new GA will provide similar results for large real-life problems. Keywords: Group Technology, Manufacturing Cell Formation, Graph Partitioning, Graph Cuts, Genetic Algorithm, Encoding representation.