Extending augmented Lagrangian coordination for the optimal configuration of cloud-based smart manufacturing services with production capacity constraint

Cloud manufacturing (CMfg) has been widely recognized since production resources could be encapsulated into smart manufacturing services and managed by advanced information and manufacturing technologies. As a core part for promoting sustainable production processes, manufacturing service configuration (MSC) aims to optimize the allocation of services for tasks in CMfg. This research studies an MSC problem considering the decision autonomy (DA) and limited production capacities (PC) of service providers (MSC-DA-PC). Augmented Lagrangian coordination (ALC), an emerged distributed optimization method, can support open-structure collaboration and allow participants to maintain decision autonomy. In this paper, ALC is extended to solve the proposed MSC-DA-PC problem by the introduction of a novel coordination element (“CO” element). The working logic and solution strategy of the “CO” element are investigated. Two case studies are employed to verify the effectiveness and efficiency of the extended ALC method. The observation shows the dynamic formation of MSC results along with the changing of task quantity.