Stochastic Dynamic Job Shop Scheduling with Sequence-Dependent Setup Times: Simulation Experimentation

Abstract

Stochastic dynamic job shop (SDJS) scheduling problems with sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of five dispatching rules (DRLs) in such shop from makespan, mean flow time, mean tardiness, number of tardy jobs, total setups, and mean setup time performance measures viewpoint. A discrete event simulation model of a SDJS manufacturing system is developed for investigation purpose. Five DRLs, that is, first come first serve (FCFS), shortest processing time (SPT), shortest setup time (SIMSET), earliest due date (EDD) and shortest sum of setup times and processing time (SSPT) are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 and setup time less than processing time. Results indicate that SIMSET rule provides best performance for mean flow time and number of tardy jobs performance measures. The SPT rule provides best performance for mean tardiness measure. The EDD rule is best-performing DRL for makespan, total setups and mean setup time measures.