Data-driven adaptive control paradigm of supply chain in pharmaceutical chain enterprises

Abstract

There are some problems in researches on supply chain control of pharmaceutical chain enterprises under dynamic environment. The authors establish a new paradigm of computer simulation analysis and adaptive control, the core strategies of which are data-driven and agent's computing. The paper constructs a feedback closed-loop cycle mode that is data collection and processing, data-driven mode discovery and performance identification, data-driven control output. Then an adaptive dynamic control strategy is established based on active induction and emergency intervention control. Contents of the new strategy include: supply chain modeling of pharmaceutical chain enterprises based on CAS, adaptive control paradigm of supply chain in pharmaceutical chain enterprises, program design of control and system behavior assessment based on epsilon machine. © 2013 Springer-Verlag.