Brown, Andrew Alexander Harold2014-11-112014-11-112014-11-112014-11-06http://hdl.handle.net/10012/8940Motivated by a situation observed by our industry partner, we test if changing dispatch methods within a job-shop can reduce the percentage of late jobs while not reducing the maximum lateness across all jobs, the two key performance indicators (KPIs) of interest. Using data provided by our industry partner, we show that the earliest operation due date (EODD) dispatch rule is the best rule for them. In addition, we propose an alternative idea for random job shop data, the routing distribution, and we compare dispatching rules performance using KPI frontiers under different routing distributions. We find that EODD is one of several dispatching rule which consistently lie on the KPI frontier for different job routing distributions. We further show that using multiple dispatch rules across several job-shop departments does improve a job-shop’s performance on the KPIs, though the improvement is small. Lastly, we leave the readers with some insight into determining which dispatch rules should be considered for different job-shops.enJob-Shopdispatching rulesimulationMaster ThesisManagement Sciences