Decision support tool for job shop scheduling with job cancellation

Abstract

Although most job shop scheduling problems are concerning dynamic demand and stochastic processing time, the majority of existing scheduling techniques are based on static demand and deterministic processing time. As a consequence, the solutions obtained from the traditional scheduling technique are ineffective wherever changes occur to the system. The Decision Support Tool (DST) for dynamic job shop scheduling was developed. The components of DST, namely, the knowledge-base, data-base, rule base, and graphical user interface were integrated. It provides alternative recommended schedules to be selected by practitioners with minimum knowledge in job shop scheduling. Validation of DST shows that the performance of DST is promising and able to provide comparable results as when using discrete event simulation. This paper demonstrates the capability of the DST to handling changes in demand, i.e. job cancellation. The demonstration suggests that the proposed DST can effectively handle job cancellation during early, middle or late time instances.