Transportation resilience optimization from an economic perspective at the pre-event stage

Since disruptive events can cause negative impacts on a city's regular traffic order and economic activities, it is crucial that a transport network is resilient against disaster to prevent significant economic losses and ensure regular social, economic, and traffic order. However, using the transport metric for resilience improvement can only provide a limited view of transport pre-investments. This study develops an optimization framework to tackle the problem of resilient road pre-investment with the aim of resilience enhancement of traffic systems from an economic perspective by applying the integrated computable general equilibrium (CGE) model. First, we use the Shapley value, which considers road links’ interact cooperation, to determine critical candidate links that need to be upgraded. Second, we propose the Economic-based Network Resilience Measure (ENRM) as a performance indicator to evaluate network-level resilience from the economic perspective. Third, a bi-level multi-objective optimization model is formulated to identify the optimal capacity improvement for candidate critical links, where the objectives of the upper-level model are to minimize the ENRM and pre-enhancement budget. The lower-level model is built on the integrated CGE model. The genetic algorithm approach is used to solve the proposed bi-level model. A case study of the optimization framework is presented using a simplified Sydney network. Results suggest that a higher budget can help promote people's social welfare and improve transportation resilience. However, the Pareto-optimality is observed, and the marginal utility decreases with an increase in the investment budget. Further, the results also show that investment returns are higher in severe disasters. This study will help transport planners and practitioners optimize resilience pre-event investment strategies by capturing a wider range of project impacts and evaluating their economic impacts under general equilibrium rather than partial economic equilibrium, which is often assumed in traditional four-step transport planning.