Solving the part families problem in discrete-parts manufacture by simulated annealing

In the production planning and control of discrete-parts manufacture, aggregation of parts into families, on the basis of similarity, is carried out to ease both long-horizon planning and short-horizon scheduling. Additional advantages are related to those of group technology (GT), such as simplifying the flow of parts and tools and reducing both set-up and production costs. The problem of formally forming part families is presented and discussed. Previous work is reviewed and assessed. Two solution approaches, one based on a location model, the other on simulated annealing, are presented and compared along with test results. The location formulation, which results in an integer programming model solved by Lagrangian relaxation, proved capable of producing solutions of excellent quality, but only for relatively small problem instances. In contrast, simulated annealing, which is a general heuristic approach to combinatorial optimization, produced solutions of comparable quality and could handle realistically large problem instances. However, careful design of the simulated annealing algorithm is crucially important. An effective design is presented.