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Constrained Optimization: Point of Dispense distribution under large scale health emergencies for Allegheny County modeled as Two-Stage Stochastic Optimization

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POD_DABP

Constrained Optimization: Point of Dispense distribution under large scale health emergencies

Strategic models have been implemented to respond to large-scale emergencies. Under the impact of COVID-19, a well-established healthcare system with preparedness and quick response has proved its necessity. Thus, a simulation of an effective pandemic preparedness significantly benefits the entire community should the COVID-19 pandemic persists or a future pandemic outbreak happens. Our model studies the construction of a medical countermeasure supply chain for Allegheny County that involves the pre-positioning of Point of Dispense (PODs), which serve as single dispatch medicine points to assigned localities. Using data from Allegheny Capital Budget Summary[1], Allegheny County Zip Code Boundaries[3], and POD sites[4], we show the pre-positioning plan that minimizes the distance required to transfer medicines from hospitals to PODs and from neighborhoods to the assigned POD.

We use Gurobi and Python to implement our model formulation.

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Constrained Optimization: Point of Dispense distribution under large scale health emergencies for Allegheny County modeled as Two-Stage Stochastic Optimization

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