Deployment or distribution of valuable medical resources has emerged as an increasing challenge to hospital administrators and health policy makers. The hospital emergency department (HED) census and workload can be highly variable. Improvement of emergency services is an important stage in the development of the healthcare system and research on the optimal deployment of medical resources appears to be an important issue for HED long-term management. HED performance, in terms of patient flow and available resources, can be studied using the queue-based approach. The kernel point of this research is to approach the optimal cost on logistics using queuing theory. To model the proposed approach for a qualitative profile, a generic HED system is mapped into the M/M/R/N queue-based model, which assumes an R-server queuing system with Poisson arrivals, exponentially distributed service times and a system capacity of N. A comprehensive quantitative mathematical analysis on the cost pattern was done, while relevant simulations were also conducted to validate the proposed optimization model. The design illustration is presented in this paper to demonstrate the application scenario in a HED platform. Hence, the proposed approach provides a feasibly cost-oriented decision support framework to adapt a HED management requirement.

Cost item is one of the main issues that will drive the design of logistics on cloud computing (CC), especially of those devoted to provide services in a long-term and steady manner. The high availability of cloud platform has emerged to an essential requirement for CC business. To keep the service level agreement committed to cloud customers, the CC platform should adopt necessary cloud logistic approach to backup breakdown servers. Aiming at searching for a feasible architecture with optimal running cost, two control parameters of standbys and repairmen in the cloud logistics has been considered to maintain regulated service quality for the cloud enterprise. Based on the queuing theory, quantitative exploration with MRP (Machine Repair Problem) model has been adopted and conducted for optimal methodology. The proposed cloud logistic framework has been designed in systematic profile. Comprehensive mathematical materials have been elaborated in details between cost pattern and system availability. Relevant numerical experiments have been conducted to verify the feasibility for trade-off between cost and availability as well. On engineering application, the proposed approach indeed provides a feasibly cost-effective decision-making support to adapt cloud-based logistics.