Abstract
Since disruptive events can cause negative impacts on a city's regular traffic order and economic activities, it is crucial that the transport network is resilient against disaster to prevent significant economic losses and ensure regular social, economic and traffic order. This study tackles the problem of resilient road pre-investment with the aim of resilience optimisation of traffic systems. First, we use the Shapley value to determine the critical candidate links that needs to be upgraded. Second, we proposed the Economic-based Network Resilience Measurement (ENRM) as a performance indicator to evaluate the network level resilience from the economic perspective. Third, a bi-level multi-objective optimisation model is formulated to identify the optimal capacity improvement for candidate critical links, where the objectives of the upper-level model are to minimise the ENRM and pre-enhancement budget. The lower-level model is the integrated computable general equilibrium (CGE) model that includes the CGE sub-model, which can be applied to capture economic impacts and traffic sub-model that optimises travelers’ behaviors under user equilibrium conditions. Genetic Algorithm (GA) heuristic approach is used to solve the proposed bi-level model. A case study of the optimisation framework is presented using a simplified Sydney network. Results suggest that ENRM decreases with the increase in investment. However, the Pareto-optimality is observed and the marginal utility decreases with the increase in investment budget. Furthermore, the more severe the disaster, the greater the marginal utility of investment.
