The design of a cellular manufacturing system requires that a part population, at least minimally described by its use of process technology (part/machine incidence matrix), be partitioned into part families and that the associated plant equipment be partitioned into machine cells. At the highest level, the objective is to form a set of completely autonomous units such that inter-cell movement of parts is minimized. We present an integer program that is solved using a genetic algorithm (GA) to assist in the design of cellular manufacturing systems. The formulation uses a unique representation scheme for individuals (part/machine partitions) that reduces the size of the cell formation problem and increases the scale of problems that can be solved. This approach offers improved design flexibility by allowing a variety of evaluation functions to be employed and by incorporating design constraints during cell formation. The effectiveness of the GA approach is demonstrated on several problems from the literature.

The Facility Layout Problem (FLP) concerns minimising total traffic cost between facilities in a particular location under given conditions including facility size and traffic between each pair of them. Because of its NP-completeness, many suboptimal methods, which look for reasonably good solutions, have been suggested. Although many papers exist which compare the performance of these methods with each other, the work is limited in the following ways: benchmark tests were done only on FLPs consisting of identical facilities; most of the algorithms being compared relied on deterministic approaches. Genetic Algorithms (GAs), which use a stochastic approach, have been used with some success for a number of NP-complete problems, typically finding good answers but not necessarily the best. However, a range of other approaches, from traditional operations research to simulated annealing, are possible. Moreover, a GA itself can be varied in many ways. So, in this research project, not only t...

this paper is to provide a review and comparison of the approaches to multi-criteria decision-making (MCDM) in the design of manu - facturing cells. A brief description of existing classi cations is provided, together with an overview on the MCDM. Selected papers are reviewed and a structured scheme is outlined which allows comparison of inputs, criteria, solution approaches and outputs across selected models. Finally the models are discussed and directions for new avenues of work are identi ed