This paper presents an insight on genetic algorithm (GA) encoding representations applied to graph partitioning problems. Redundancy and blindness, two important features that have a direct impact on the performance of the method, are theoretically investigated and some conclusions are drawn.
This paper deals with manufacturing cell formation considering the dynamic behavior of the production system. First, we discuss the importance of taking into account the dynamic aspect of the problem that has been poorly studied in the related literature. We argue that by considering a multi-periodic planning horizon, we can tackle the problem according to… (More)
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… (More)
This paper deals with a fuzzy genetic algorithm applied to a manufacturing cell formation problem. We discuss the importance of taking into account the dynamic aspect of the problem that has been poorly studied in the related literature. Using a multi-periodic planning horizon modeling, two strategies are considered: passive and active. The first strategy… (More)
Cell formation is one of the main problems to be solved when dealing with cellular manufacturing. An exact graph theory based Branch & Bound method has been proposed by the authors . In this paper we tackle the problem by considering two objectives: minimizing both intercellular movements and workload unbalance. We argue that when an epsilon-constraint… (More)