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A Fuzzy Gradient Chance-Constrained Evacuation Model for Managing Risks under Uncertain Climatic and Environmental Conditions
Emergency evacuation is one of the most important risk management measures for nuclear accidents. Evacuation management systems contain various complexities, which have posed many challenges for decision makers. In the study, a fuzzy gradient chance-constrained evacuation model (FGCCEM) is proposed to address different uncertainties in evacuation management and planning. The FGCCEM is developed by incorporating fuzzy gradient chance-constrained programming into an inexact optimization framework. It is capable of balancing decision makersâ€™ optimism and pessimism, and can also reflect uncertainties expressed as discrete intervals. The proposed model is applied to a hypothetical case study of emergency evacuation planning for nuclear power plants. The results indicate that the FGCCEM can generate optimized evacuation schemes to maximize the total number of evacuees within limited time. Meanwhile, evacuation schemes with decision makersâ€™ varied preferences can be obtained through post-optimization analysis. The information obtained in this study can provide an insight into the complex relationships in evacuation management systems. It can also provide valuable decision support for effective risk management in response to nuclear emergencies.
Keywords: evacuation management, fuzzy gradient chance-constrained programming, optimization, uncertainty, nuclear power plants,
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