For supply chain optimization, as a key determinant of strategic resources mobility along the value-added chain, simulation is widely used to test the impact on supply chain performance for the strategic level decisions, such as the number of plants, the modes of transport, or the relocation of warehouses. Traditionally, a single centralized model that encompasses multiple participants in the supply chain is built when optimization of the supply chain through simulation is required. However, due to the heterogeneity of supply chain, a centralized simulation model has a limit to reflect the dynamics of each supply chain participant. This research focuses on the conceptual and the technical issues about the supply chain simulation with a parallel and distributed simulation (PADS) concept. In particular, to ensure the decomposition of supply chain simulation model by each supply chain participant, the simulation framework is proposed using Service Oriented Architecture (SOA) in e-collaboration environment. For a clear proof of concept, the virtual supply chain simulation model is implemented and experienced using business process modeling tools in SOA. Due to the reusable, interoperable, and scalable characteristics of the proposed supply chain simulation framework, various alternatives for supply chin optimization can be generated and evaluated.
Bypassing Data Issues of a Supply Chain Simulation Model in a Big Data Context
