A Simulation-Based Sequential Search Method for Multi-Obejctive Scheduling Problems of Manufacturing Systems

Abstract

A scheduling method based on a combination of dispatching rules is often used in dynamic and flexible manufacturing systems to consider changing production environments. A weighted sum method, which assigns weights to dispatching rules and selects the job that has the largest weighted sum as the next job, is frequently used in LCD or semiconductor manufacturing systems. The weights of dispatching rules in each process stage are determined by fab engineers and adjusted periodically to reflect the current state of the system. Fab engineers choose appropriate weights based on their experiences to improve multiple objectives, such as maximization of throughput and minimization of setup times simultaneously. In this study, we propose a systematic sequential search method for dispatching rule weights to provide Pareto-front solutions. The proposed method divides a search space into sub-spaces with decision tree methods generated for each objective and also uses surrogate models to estimate objective values.