Resource allocation methodology based on object-oriented discrete event simulation: A production logistics system case study

2020 ◽  
Vol 31 ◽  
pp. 394-405 ◽  
Author(s):  
Guangzhen Li ◽  
Shengluo Yang ◽  
Zhigang Xu ◽  
Junyi Wang ◽  
Zhaohui Ren ◽  
...  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.


Author(s):  
Ming Dong ◽  
Jianzhong Cha ◽  
Mingcheng E

Abstract In this paper, we realize knowledge-based discrete event simulation model’s representation, reasoning and implementation by means of object-oriented(OO) frame language. Firstly, a classes library of simulation models is built by using the OO frame language. And then, behaviours of simulation models can be generated by inference engines reasoning about knowledge base. Lastly, activity cycle diagrams can be used to construct simulation network logic models by connecting the components classes of simulation models. This kind of knowledge-based simulation models can effectively solve the modeling problems of complex and ill-structure systems.


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