## 5 Conclusions  
In this study, we explore a GIMRPMTWIFCCTR, in which the economic, environmental, and reliability objectives are comprehensively considered. Based on the use of IFNs to model uncertainty, we propose an IFLOM to address the specific routing problem and further present its crisp reformulation, in which the optimization level is introduced to indicate the receiver's attitude towards the RT. The following conclusions are drawn:  
1. Modeling the capacity and carbon tax rate uncertainty in the GIMRP and introducing the optimization level in the crisp processing of the IFLOM enable the different decision-making attitudes of receivers to be fully measured, improve the flexibility of the routing decision-making, and avoid unreliable transportation;
2. Achieving a reliable intermodal route through improving the optimization level worsens both the economic and environmental sustainability of the route. Therefore, the receiver must select a suitable optimization level to balance these objectives based on their attitude towards the RT, their budget, and their willingness towards CE reduction;
3. An MTW is more feasible than the HTW and STW in ensuring the timeliness of GIMRP. Therefore, in the routing stage, the receiver should accurately determine their tolerable and expected time windows to establish an MTW that matches the post-transportation processing of good;
4. Under an uncertain carbon tax rate, CTR is not feasible in all decision-making scenarios. When CTR is infeasible, the BOO can be used by the IMO and receiver to balance the economic and low-carbon objectives of the GIMRP;
5. The release time of containers influences the GIMRPMTWIFCCTR to a certain degree. An earlier release time can help the receiver to reduce the TCs of the PIMR that maintains a high RT, which relies on effective negotiation between the shipper and the receiver.
6. The stability of the interval fuzzy capacity also influences the GIMRPMTWIFCCTR to a certain degree. The IMO should improve the capacity stability of the intermodal network to provide the receiver with a transportation service that yields both lower TCs and higher RT.  
The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/asi8030068/s1](https://www.mdpi.com/article/10.3390/asi8030068/s1)]([https://www.mdpi.com/article/10.3390/asi8030068/s1](https://www.mdpi.com/article/10.3390/asi8030068/s1)), Table S1: Travel distances in km and maximum possible capacities in TEU of the transportation modes on the arcs; Table S2: Maximum possible capacities in TEU to transfer containers between transportation modes at the transfer nodes; Table S3; Speeds and carbon emission factors of transportation modes; Table S4: Cost rates in CNY/TEU, times in h/TEU, and carbon emission factors in kg/TEU to transfer containers between transportation modes.  
Conceptualization, Y.G., Y.S. and C.Z.; data curation, Y.G. and Y.S.; formal analysis, Y.G., Y.S. and C.Z.; funding acquisition, Y.S.; investigation, Y.G., Y.S. and C.Z.; methodology, Y.G., Y.S. and C.Z.; resources, Y.G. and Y.S.; software, Y.G., Y.S. and C.Z.; validation, Y.G., Y.S. and C.Z.; writing--original draft, Y.G. and Y.S.; writing--review and editing, Y.G., Y.S. and C.Z. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study was funded by the Shandong Provincial Natural Science Foundation of China under Grant No. ZR2023 MG020 and the Shandong Provincial Social Science Planning Research Project of China under Grant No. 21 DGLJ08.  
**Data Availability Statement:** All data generated or analyzed during this study are included in this paper.  
**Conflicts of Interest:** The authors declare no conflicts of interest.