  The machine-part cell formation problem consists of creating machine cells
and their corresponding part families with the objective of minimizing the
inter-cell and intra-cell movement while maximizing the machine utilization.
This article demonstrates a hybrid clustering approach for the cell formation
problem in cellular manufacturing that conjoins Sorenson s similarity
coefficient based method to form the production cells. Computational results
are shown over the test datasets obtained from the past literature. The hybrid
technique is shown to outperform the other methods proposed in literature and
including powerful soft computing approaches such as genetic algorithms,
genetic programming by exceeding the solution quality on the test problems.
