Reengineering the order fulfillment process in supply chain networks

An order fulfillment process (OFP) starts with receiving orders from customers and ends with delivering the finished goods. The order fulfillment process is complex because it is composed of several activities, executed by different functional entities, and heavily interdependent among the tasks, resources, and agents involved in the process. A supply chain network (SCN) is a network of autonomous or semi-autonomous business entities involved, through upstream and downstream links, in the different processes and activities that produce goods or services to customers. As manufacturing practice shifts toward the outsourcing paradigm, the OFP is more likely to be executed throughout SCNs. It becomes imperative to integrate the OFP into SCNs to improve the OFP. Generalizing from the variety and complexity of SCNs, this study identifies several main types of SCN structures and addresses OFP issues based on them. The objective of reengineering the OFP is to achieve agility in the process in terms of efficiency, flexibility, robustness, and adaptability. We propose a multiagent information system (MAIS) approach for reengineering the OFF in SCNs. The MAIS models the OFP in SCNs and evaluates OFF performance by applying the proposed strategies. A multiagent simulation platform, called Swarm, is enhanced and applied for modeling the MAIS; and experiments are conducted to simulate the OFP and then evaluate the potential improvement strategies to identify useful strategies for improving the OFP. The strategies we evaluated include (1) coordinating demand management policies, (2) information sharing strategies, (3) synchronizing material and capacity availability, (4) dynamic resource allocation, and (5) the combination of various strategies. The results shed light on identifying the main effects of various strategies on OFP performance. The insights from utilizing various strategies in different SCNs help reengineer the OFP in SCNs.