Effect of sequencing rules on order release policies in a stochastic and dynamic job shop with sequence-dependent setup times – a simulation study

Abstract

Order review and release in job shop with sequence-dependent setup times is one of the most complex job shop scheduling problems. This article analyses the effect of sequencing rules on different order release policies for performance measures i.e. mean throughput time, total setups, mean setup time, number of tardy jobs and makespan in a stochastic and dynamic job shop with sequence-dependent setup time. Four sequencing rules, viz. first-come-first-serve, planned release date, earliest due date, shortest processing time and five order review and release policies i.e. aggregate workload trigger, workcentre workload trigger, corrected workload trigger, upper bound release and lancaster university management school corrected order release are taken into consideration. A simulation model using Promodel® is developed for experimental purpose. Results indicate that for a given order review and release policy, there is an effect of sequencing rule in a stochastic and dynamic environment with consideration of sequence-dependent setup time and the best performing sequencing rule is different for different order review and release policies for a given performance measure.