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This paper aims to propose a comprehensive equilibrium service capability recovery model to effectively recover the service capability of a port-hinterland service network with delay or disruption risk under limited resources. We first analyze the risk factors and generation mechanism of a port-hinterland network and then introduce a differential evolution algorithm and project pursuit method to determine the risk resistance level of service nodes and regions in a port-hinterland service network for resource allocation and service capability recovery based on the selected indicators. An equilibrium utility model is used to control the equilibrium of the service capability recovery within nodes and regions in the port-hinterland service network, and the multinomial logit model is used to calculate the service path choice probability. Finally, we build this model, taking the port-hinterland service network of three provinces in Northeast China as examples to validate the model, which is solved with an elite genetic algorithm, and then perform comparisons of four scenarios. The results show that (1) external factors more easily induce delay or disruption risk than do internal factors; (2) the strategy considering equilibrium recovery is better than that without considering equilibrium recovery; (3) the strategy considering both equilibrium among the regions and inside the regions is better than that considering only region equilibrium or internal equilibrium; and (4) the strategy considering region equilibrium is better than that considering internal equilibrium.

An Equilibrium Service Capability Recovery Model for a Port-Hinterland Service Network With Delay or Disruption Risk