Parameter setting of the Fuzzy ART neural network to part–machine cell formation problem

Abstract

The first step in cellular manufacturing system applications is the solution of the cell-formation problem. Many researchers have investigated this problem and a number of methods developed. In the present study, one of these methods, the Fuzzy ART neural network, was investigated. This method can solve the cell-formation problem using both binary and non-binary part-machine incidence matrices. The neural network model was coded in PASCAL and applied to 26 test problems to determine the efficient parameter combinations. Results show that the Fuzzy ART neural network can solve both binary and non-binary problems effectively. Results also show that’ parameter combinations for binary problems differ from parameter combinations for non-binary problems.