A multi-objective optimization model to minimize the evacuation time during a disaster considering reconstruction activity and uncertainty: A case study of Cork City

Abstract

Disasters can potentially disrupt transportation systems, resulting in complete or partial blockages of specific links, which can limit the available options for transportation. During a disaster, crucial decisions must be made, such as planning the safe evacuation of people from affected areas and strategizing to repair damaged transportation links. The primary objective of this research is to develop a multi-objective optimization framework that can enhance the effectiveness of transportation networks in natural disasters, such as floods. To achieve this, the proposed model incorporates fuzzy set theory since it is challenging to determine parameters like capacity precisely in these situations. The model assumes that some damaged links can be reconstructed within the available resources and budget. The optimization model focuses on minimizing the total evacuation time and reconstruction cost, and its effectiveness is validated using a case study of Cork City with 100 nodes and 141 links. The model is solved, and optimal solutions are generated using an exact method to handle various uncertainty scenarios. The results demonstrate that developing the fuzzy optimization approach as an analytical tool can be used to make critical decisions for evacuation planning and emergency management.