Grouping genetic algorithms: An efficient method to solve the cell formation problem

The layout problem arises in a production plant during the study of a new production system, but also during a possible restructuring. The main aim of layout design is to reduce transportation and maintenance, which simplifies management, shortens lead time, improves product quality and speeds up the response to market fluctuations. A principle of Group Technology (GT) advocates the division of a unity into small groups or cells. As it is most of the time impossible to design totally independent cells, the problem is to minimise traffic of items between the cells, for a fixed maximum cell size. This problem is known as cell formation problem (CFP). We propose here an original approach to solve this NP-hard problem. It is based on a Grouping Genetic Algorithm (GGA), a special class of genetic algorithms, heavily modified to suit the structure of grouping problems. The crucial advantage of this GGA is that it is able to deal with large instances of the problem thus becoming a powerful tool for an engineer determining a plant layout, allowing him or her to try several plant options, without the limitation of huge computation times. © 2000 IMACS/Elsevier Science B.V. All rights reserved.SCOPUS: ar.j