Lot Splitting in Stochastic Flow Shop and Job Shop Environments

This paper studies various lot splitting policies in stochastic job shop and flow shop settings with the objective of minimizing long-run mean flow time (MFT).Using a simulation model, we estimate MFT for each policy in stochastic, dynamic situations.When lot splitting is combined with repetitive lots priority, MFT decreases, but there are few differences between the exact lot splitting policy used.Thus, in stochastic, dynamic situations the use of lot splitting is more important than the exact method used.Methods which perform well in static, deterministic environments do not necessarily perform well in other scenarios.We conclude our analysis with a discussion of our findings in relation to flow dominance and JIT/kanban issues.