Statistical model checking of relief supply location and distribution in natural disaster management

Abstract Examining the efficacy of natural disaster management readiness and response activities is challenging due to the involvement of many random and uncertain components. These uncertainties can be captured by stochastic models. The analysis of these models is carried out using Monte Carlo simulations to judge the effectiveness of natural disaster management solutions. However, this approach uses static estimators, which generally rely on sampled number of events taken from the random space. The safety-critical nature of disaster management requires a more quantifiable analysis. In order to overcome this challenge, we propose to use statistical model checking for relief supply location and distribution in natural disaster management. For illustration purposes, we use the PRISM model checker to model and analyze a real-world scenario of relief supply location and distribution while considering some key factors, like demand of medical supplies at hospitals, predestined routes from warehouses to hospitals, capacity of warehouses and transportation plans.