Parallel discrete event simulation algorithm for manufacturing supply chains

Abstract

Parallel discrete event simulation (PDES) is concerned with the distributed execution of large-scale system models on multiple processors. It is an enabler in the implementation of the virtual enterprise concept, integrating semi-autonomous models of production cells, factories, or units of a supply chain. The key issue in PDES is to maintain causality relationships between system events, while maximizing parallelism in their execution. Events can be executed conservatively only when it is safe to do so, sacrificing the extent to which potential parallelism of the system can be exploited. Alternatively, they can be processed optimistically without guarantee of correctness, but incurring the overhead of a rollback to an earlier saved state when causality error is detected. The paper proposes a modified optimistic scheme for distributed simulation of constituent models of a supply chain in manufacturing, which exploits the inherent operating characteristics of its domain.