Efficient evacuation routing and allocation of evacuees to safe shelters can effectively reduce casualties and property losses caused by storm surge disasters. A biobjective model is proposed to tackle shelter allocation and emergency routing problems while simultaneously considering network reliability. The proposed model maximizes the total reliability of routes connecting residential communities and shelters and those connecting shelters. A nondominated sorting genetic algorithm is developed to solve this biobjective model with a specially designed chromosome structure, initialization process, and genetic operators. The mathematical model is validated with a case study using storm surge scenario simulation data and real-world community and infrastructure data from Pingyang County, China. The case study illustrates the effectiveness of the proposed model and its potential application in real-world disaster risk reduction.
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