An iterated local search heuristic for cell formation

An iterated local search (ILS) heuristic to maximize grouping efficacy is presented.A comparative study was completed assuming residual cells are forbidden.A comparative study was completed assuming residual cells are permitted.The ILS heuristic is competitive with sophisticated metaheuristics from the literature.Test problems and software are provided in an online supplement. The grouping efficacy index (GEI) has emerged as the most popular objective criterion for part-machine clustering problems associated with manufacturing cell formation. A variety of metaheuristics have been proposed for cell formation based on the GEI, including methods such as simulated annealing, tabu search, genetic algorithms, variable neighborhood search, and water flow-like algorithms. In this paper, we develop and implement an iterated local search (ILS) heuristic that has proved effective for a variety of different combinatorial optimization problems. Computational results revealed that the ILS generally matches the optimal (or best known) solutions for 37 test problems from the literature. An inherent advantage of the ILS is its simplicity. All test problems, along with the Fortran source codes and executables for the ILS heuristics under the assumptions of forbidden and permitted residual cells, are available from an internet website associated with the manuscript.

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