On Solving Large-Size Generalized Cell Formation Problems via a Hard Computing Approach Using the PMP

Abstract

In this paper, we show that the hard computing approach using the p-median problem (PMP) is a very effective strategy for optimally solving large-size generalized cell formation (GCF) problems. The soft computing approach, relying on heuristic or metaheuristic search algorithms, has been the prevailing strategy for solving large-size GCF problems with a short computation time at the cost of the global optimum in large instances of GCF problems; however, due to recent advances in computing technology, using hard computing techniques to solve large-sized GCF problems optimally is not time-prohibitive if an appropriate mathematical model is built. We show that the hard computing approach using the PMP-type model can even solve large 0–1 GCF instances optimally in a very short computation time with a powerful mixed integer linear programming (MILP) solver adopting an exact search algorithm such as the branch-and-bound algorithm.