The current study presents a novel method for mitigating the consequences of disturbances in gas transmission systems (GTSs). The method presented was developed during the SecureGas project for identification of critical infrastructure and risk and resilience analysis. The method determines the optimal response strategies consisting of detailed coordination of demand curtailment for consumer nodes and the use of available reserve gas sources. Key characteristics of the method are an ability to adapt the modelling complexity for a particular task or a network part and several computational time economy measures making the method practical for large GTSs. The method can simultaneously consider variations of demand rates, consumer group compositions, source capacities, and average temperature and density of the gas in user-defined network parts during one or multiple concurrent disruptions in a GTS with different element restoration times. Preliminary analysis of a GTS model, which dynamically excludes network parts that are impossible to supply, implementation of a tailored genetic algorithm and supplemental sub-algorithms are used to save computation time while providing an optimal so- lution. A robust hydraulic steady-state solver is utilised for verification of solution feasibility in combination with dynamic changes to a GTS model implementing an adaptive network-wise control of multi-directional compressor stations and pressure regulators during different disturbance states of a GTS. A case study using a model of a real GTS demonstrated the effects of consumer categorisation and different modelling complexities, possible to consider with the developed method, on the estimated consequences of several types of disturbances and actions necessary to mitigate them by creating optimal response strategies.