Comparative Study of Evolutionary Techniques for Design of Cellular Manufacturing Systems

摘要

Cellular manufacturing system (CMS) couples the flexibility of job shops with high production rate of flow lines. The basic idea of CMS is to break up a complex manufacturing facility into several groups of machines called cells. Each cell is being dedicated to the processing of a group of parts called part family. Therefore, ideally, each part type is produced in a single cell. Thus, material flow is simplified and the scheduling task is made much easier. The benefits resulting from CMS can be substantial. However design of CMS is not a simple task. Over the past three decades, many methodologies were used to design the CMS. In recent past, meta-heuristic approaches are widely used in design of CMS. In this work, Genetic algorithm and particle swarm optimization were used to design the CMS. Problems with different sizes from the literature were used to evaluate the methods. From the results obtained it was observed that the overall performance of the genetic algorithm presented in this paper is superior to the particle swarm optimization.