Using simulated annealing to select least-cost assembly sequences

Applies simulated annealing (SA) to find the probable least cost assembly sequence for a mechanical product from among the thousands of feasible sequences. The sequences are represented by the assembly sequence network introduced by De Fazio and Whitney (1987). Candidate sequences are selected one at a time by the SA algorithm and their cost is estimated by designing a minimum unit cost concept assembly system using a dynamic programming algorithm. Alternate sequences are selected by perturbing the path through the sequence network in a way similar to a genetic algorithm. This method differs from that normally used to select least cost sequences, in which an engineer edits the thousands of sequences using judgment and experience, and then obtains the costs of a few that survive editing. Here, the search for a least cost sequence is done without prior editing. In the examples studied, there appear to be a large number of sequences that are technically quite different but of similar cost