The optimal intermodal nodes and routes are two of the most challenging issues for intermodal participants. We present a two-phase approach that includes the fuzzy c-means clustering method (FCM) and a multi-objective optimization model to solve intermodal location-routing issues. A weighted sum technique and a genetic algorithm (GA) are designed to address this model. The two-phase approach is beneficial in meeting different market demand preferences of intermodal participants. It also has applications in solving the sustainable intermodal location-routing problems, further solving the network optimization problem in large-scale scenarios. A typical intermodal transport network in the Bohai Rim region is used to verify the effectiveness of this approach. The results provide references for the participants in the Bohai Rim region to choose the optimal intermodal nodes and routes. The findings also offer theoretical insights for optimizing intermodal networks in other regions of China, with goals of improving sustainable transport efficiencies.

The rise of value networks in the new economic era and the emergence of a common competitive advantage pose enormous challenges to the value-added approach of enterprises based on traditional value chains. Based on the customer-centered concept, the complementary effect of agents, and other competition characteristics of the value network, this paper constructs a multi-agent-based value network evolution model. The influencing mechanism of customer preference on the number of value network entities and overall income is discussed through simulation analysis. The research shows that the influence of customer preference on the evolution and steady-state of the overall value of the value network is not significant. Customer preference plays a decisive role in the number of service subjects and the evolution of attributes. In different situations, the influence of customer preference on the number of subjects is significantly different. This means that customer power preference in the value network of port services is much higher than other preferences. The research results provide a decision-making basis for enterprises to break through the shackles of traditional value-added concepts, actively seek value network optimization schemes, and achieve timely responses to customer preferences.