Optimisation model for short-term road network resilience restoration considering heterogeneous travellers under sudden events

The increasing frequency of emergencies challenges urban transportation network resilience, necessitating efficient restoration within the resource-constrained ‘golden rescue period.’ Existing research often decouples physical infrastructure repair (‘hard repair’) from traffic management (‘soft repair’) and overlooks travellers’ bounded rationality under incomplete information. This study proposes a ‘soft-hard coordination’ optimisation model for post-disaster network recovery. The model co-optimises physical restoration schedules and traffic management intensity to maximise network resilience, quantified by an improved natural connectivity metric. A bi-level programming framework is formulated: the upper level optimises coordinated strategies while the lower level employs Stochastic User Equilibrium to simulate boundedly rational travellers’ route choices, solved via a hybrid SA–PSO algorithm. A case study of Yuzhong District, Chongqing, shows that the resilience-first strategy repairs nine damaged segments and achieves a resilience index of 0.7541. Greater information-intervention intensity further improves resilience, demonstrating that coordinated traffic guidance can complement limited physical repair. The framework provides quantitative support for short-term urban network recovery and emergency resource allocation.