Distributionally Robust Optimization of Vaccination Site Location Problem under Decision-dependent Uncertainty
Considering that residents'willingness to receive vaccines is often influenced by vaccination site location decisions,a new method was proposed to address the vaccination needs with decision-dependent uncertainty.Firstly,a decision-dependent fuzzy set based on moment information was constructed to model the distribution of vaccination demands,and the mean and variance of each random vaccination demand were expressed as a piecewise linear function of location decision.Secondly,the minimum vaccination amount was introduced at each demand point,and a distributionally robust optimization model was proposed for vaccination site location under uncertain demand.Finally,two propositions were proposed and proved by using the robust equivalence theory.Combined with McCormick envelope method,the model was reformulated into a mixed integer linear programming model.The results of testing and sensitivity analysis indicate that this model can achieve a balance between economic and social benefits,thereby providing decision support for the reasonable layout of vaccination sites in uncertain environments.
decision-dependent uncertaintyvaccination site locationdistributionally robust optimizationmixed-integer linear programming