Identification of optimal plans for event-related evacuation under fuzziness environment

Occurrence of large-scale events has been increasingly common across the world, requiring essential tools for evacuating the involved people. In this study, an inexact optimization model for event-related evacuation management is developed (IEM-FE: inexact evacuation model under fuzzy environment). In the model, comprehensive considerations of system efficiency, economic cost and environmental protection during evacuation are incorporated within a general framework, without overemphasizing one issue at the expense of neglecting the others. Also, through fuzzy robust programming and interval linear programming approaches, ambiguous and vague information can be effectively handled, highly improving robustness of the developed model. Thus, uncertainties of transportation factors and processes can be effectively communicated into the optimization process and resulting solutions. The developed model has been applied to a case study. Reasonable and useful solutions have been obtained, representing compromised plans for vehicle allocation and routing under varied objectives. The results suggest that the proposed method can explicitly address uncertainties and complexities in evacuation management systems and is applicable to practical evacuation problems.