Real-time optimization and control mechanisms for collaborative demand and capacity sharing

This work presents a new mechanism for real-time resource allocation, order administration, and process monitoring in Collaborative Networked Enterprises (CNE). The motivation is to mitigate the uncertainties and risks caused by arbitrary nature of customer orders, dynamic changes in demand patterns, and unforeseen supply disruptions. Enterprise collaboration is enabled by Demand and Capacity Sharing (DCS) among enterprises considering four decision criteria: (a) Total cost; (b) Demand fulfillment; (c) Resource utilization; and (d) CNE stability. A Task Administration Protocol (TAP) is designed for priority-based allocation/re-allocation of resources and real-time monitoring of DCS processes. The TAP is enhanced with a Predictive Best Matching Protocol (PBMP), which optimizes allocation decisions in real-time while taking into account potential future events. The new Real-Time Optimization (RTO) mechanism is proven in experiments to be an advantageous solution for mitigating undesirable impacts of uncertainty and dynamicity on the CNE performance with respect to the four undertaken decision criteria. •Collaboration is performed through demand and capacity sharing.•Collaboration decisions are improved via a new real-time optimization mechanism.•Cost, resource utilization, demand fulfillment rate, and stability are optimized.•New predictive control mechanisms enable higher flexibility in uncertain environments.