A supply chain is a network of entities involving an interplay of different individual behaviors. For an industrial scale supply chain, this network can be very complex. For a large scale supply chain, the structure is usually distributed with the different functions being performed both synchronously and asynchronously. A supply chain may consist of entities belonging to the same or different organizations. The behavior of the overall network evolves as a mixture of these synchronous and asynchronous business processes. In this work, we demonstrate the importance of capturing the synchronous and asynchronous decision-making strategies of different supply chain entities. We use agent based simulation models and embedded optimization models to study how the behavior of the network evolves as a result of the individual synchronous and asynchronous functions. Hybrid simulation based optimization is used to predict the optimal operation under the two scenarios. (C) 2014 Elsevier Ltd. All rights reserved.