Due-date setting methodologies based on simulated annealing—an experimental study in a real-life job shop

In this article we present a real-life study of a job shop manufacturing ball screws. The aim of the study is to suggest an efficient scheduling and due-date setting policy for the shop. Three different methodologies for setting parameter coefficients for due-date setting in a job shop are proposed. These methodologies are based on a search algorithm, simulated annealing algorithm, and a combination of simulated annealing algorithm and regression analysis. It is found that the combination of a simulated annealing algorithm with regression analysis provides better due-date estimates in minimizing the root mean square of lateness.