Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach

2017 ◽  
Vol 97 ◽  
pp. 69-96 ◽  
Author(s):  
Ayşe N. Arslan ◽  
Dimitri J. Papageorgiou
Keyword(s):  
Stochastic Programming ◽  
Programming Approach ◽  
Multi Stage

A Multi-Stage Stochastic Programming Approach to the Optimal Surveillance and Control of Emerald Ash Borer in Cities

2020 ◽  
Author(s):  
Eyyüb Y. Kıbış ◽  
I. Esra Buyuktahtakin ◽  
Robert G. Haight ◽  
Najmaddin Akhundov ◽  
Kathleen Knight ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Emerald Ash Borer ◽  
Programming Approach ◽  
Multi Stage ◽  
And Control

scholarly journals A Multi-Stage Stochastic Programming Approach to Epidemic Resource Allocation with Equity Considerations

2021 ◽  
Author(s):  
Xuecheng Yin ◽  
İ. Esra Büyüktahtakın
Keyword(s):  
Resource Allocation ◽  
Stochastic Programming ◽  
Ebola Virus ◽  
Programming Model ◽  
Virus Disease ◽  
Programming Approach ◽  
Multiple Time ◽  
Allocation Policy ◽  
Multi Stage ◽  
Constraints Model

AbstractExisting compartmental models in epidemiology are limited in terms of optimizing the resource allocation to control an epidemic outbreak under disease growth uncertainty. In this study, we address this core limitation by presenting a multi-stage stochastic programming compartmental model, which integrates the uncertain disease progression and resource allocation to control an infectious disease outbreak. The proposed multi-stage stochastic program involves various disease growth scenarios and optimizes the distribution of treatment centers and resources while minimizing the total expected number of new infections and funerals. We define two new equity metrics, namely infection and capacity equity, and explicitly consider equity for allocating treatment funds and facilities over multiple time stages. We also study the multistage value of the stochastic solution (VSS), which demonstrates the superiority of the proposed stochastic programming model over its deterministic counterpart. We apply the proposed formulation to control the Ebola Virus Disease (EVD) in Guinea, Sierra Leone, and Liberia of West Africa to determine the optimal and fair resource-allocation strategies. Our model balances the proportion of infections over all regions, even without including the infection equity or prevalence equity constraints. Model results also show that allocating treatment resources proportional to population is sub-optimal, and enforcing such a resource allocation policy might adversely impact the total number of infections and deaths, and thus resulting in a high cost that we have to pay for the fairness. Our multi-stage stochastic epidemic-logistics model is practical and can be adapted to control other infectious diseases in meta-populations and dynamically evolving situations.

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