Urban recovery management: assessment of multiple restoration priorities and the effect of damage degree using agent-based modeling

Abstract

 Present work is devoted to the problem of emergency response to a large-scale disaster and the recovery management of an urban socio-technical system. An iterative algorithm based on reactive decision-making is proposed as an approach enabling the recovery manager to test a set of potential restoration priorities using numerical simulation and agent-based modeling. The proposed method helps to coordinate reconstruction processes even in the case when the information is fluid and uncertain via providing a set of different recovery plans, the efficiency of which may be assessed using various factors. It also enables to determine how an under- or over-evaluation of the damage degree will affect the integral duration of the recovery process. As a result, the recovery manager will be supplied with a collection of possible recovery plans, which are numerically tested, visualized, and whose relative efficiency is evaluated using multiple estimators. Such an outcome enables to avoid the delay of recovery initiation caused by the ambiguity of the initial state of the system and the impossibility to define the recovery strategy right after a disaster occurrence.