In multi-echelon decentralized supply chains, distribution logistics (inclusive ofboth material and information flows) play a leading part in helping a supplychain gain advantage over competitors. The uncertain consumer demand andnon-optimal operation of distribution nodes are some of the major problems thata supply chain must contend with. A distribution node in the network generallybelongs to different companies thereby encouraging the decentralizedmanagement of nodes. Decentralized management may worsen the overallperformance of the supply chain system and in turn affect the supply chain costand customer satisfaction. Our work is focused on developing an assessmentframework to examine and enhance the performance of an existing supplychain. Data from an existing network is used to determine the bottlenecks orpoorly performing nodes. With the knowledge of supply chain architecture,time-series data analysis techniques are employed in this effort. Simulationbased optimization are extensively employed to enrich the performance of theinferior nodes close to achievable benchmark standards by minimizing thesupply chain cost. The concepts presented will be complemented by realisticsimulation examples.
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