Intermodal Simulation:
Ambrosino, D., & Sciomachen, A. (2012). Hub locations in urban multimodal networks.
Wang, H., Wang, X., & Zhang, X. (2017). Dynamic resource allocation for intermodal freight transportation with network effects: Approximations and algorithms. Transportation Research Part B: Methodological, 99, 83-112.
Tamagawa, D., Taniguchi, E., & Yamada, T. (2010). Evaluating city logistics measures using a multi-agent model. Procedia-Social and Behavioral Sciences, 2(3), 6002-6012.
Teo, J. S., Taniguchi, E., & Qureshi, A. G. (2014). Evaluation of load factor control and urban freight road pricing joint schemes with multi-agent systems learning models. Procedia-Social and Behavioral Sciences, 125, 62-74.
Crainic, T. G., Perboli, G., Mancini, S., & Tadei, R. (2010). Two-echelon vehicle routing problem: a satellite location analysis. Procedia-Social and Behavioral Sciences, 2(3), 5944-5955.
Holmgren, J., Davidsson, P., Persson, J. A., & Ramstedt, L. (2012). TAPAS: A multi-agent-based model for simulation of transport chains. Simulation Modelling Practice and Theory, 23, 1-18.
Gonzalez-Feliu, J., & Salanova, J. M. (2012). Defining and evaluating collaborative urban freight transportation systems. Procedia-Social and Behavioral Sciences, 39, 172-183.
Hillbrand, C., & Schmid, S. (2011, June). Simulation of co-operative logistics models for multimodal transportation networks. In Proceedings of the 2011 Summer Computer Simulation Conference (pp. 180-187).
Hrušovský, M., Demir, E., Jammernegg, W., & Van Woensel, T. (2018). Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty. Flexible Services and Manufacturing Journal, 30, 486-516.
Blecken, W. D. A., & Klöpfer, R. D. S. (2010). Advanced Manufacturing and Sustainable Logistics.
Sirikijpanichkul, A., FERREIRA, L., & LUKSZO, Z. (2007). Optimizing the location of intermodal freight hubs: an overview of the agent based modelling approach. Journal of transportation systems engineering and information technology, 7(4), 71-81.
Macharis, C., Caris, A., Jourquin, B., & Pekin, E. (2011). A decision support framework for intermodal transport policy. European Transport Research Review, 3, 167-178.
Herazo-Padilla, N., Montoya-Torres, J. R., Muñoz-Villamizar, A., Isaza, S. N., & Polo, L. R. (2013, December). Coupling ant colony optimization and discrete-event simulation to solve a stochastic location-routing problem. In 2013 Winter Simulations Conference (WSC) (pp. 3352-3362). IEEE.
Sinha, S., & Ganesan, V. K. (2011, December). Enhancing operational efficiency of a container operator: A simulation optimization approach. In Proceedings of the 2011 Winter Simulation Conference (WSC) (pp. 1722-1733). IEEE.
Liedtke, G. (2009). Principles of micro-behavior commodity transport modeling. Transportation Research Part E: Logistics and Transportation Review, 45(5), 795-809.
Macharis, C., & Pekin, E. (2009). Assessing policy measures for the stimulation of intermodal transport: a GIS-based policy analysis. Journal of transport geography, 17(6), 500-508.
Crainic, T. G., Perboli, G., & Rosano, M. (2018). Simulation of intermodal freight transportation systems: a taxonomy. European Journal of Operational Research, 270(2), 401-418.
Life Cycle Analysis:
Sherafati, M., Bashiri, M., Tavakkoli-Moghaddam, R., & Pishvaee, M. S. (2020). Achieving sustainable development of supply chain by incorporating various carbon regulatory mechanisms. Transportation Research Part D: Transport and Environment, 81, 102253.
Kim, N. S., & Van Wee, B. (2009). Assessment of CO2 emissions for truck-only and rail-based intermodal freight systems in Europe. Transportation planning and technology, 32(4), 313-333.
Aminzadegan, S., Shahriari, M., Mehranfar, F., & Abramović, B. (2022). Factors affecting the emission of pollutants in different types of transportation: A literature review. Energy Reports, 8, 2508-2529.
Ontology & LLM:
Rodrigues, F. H., Lopes, A. G., dos Santos, N. O., Garcia, L. F., Carbonera, J. L., & Abel, M. (2023, October). On the Use of ChatGPT for Classifying Domain Terms According to Upper Ontologies. In International Conference on Conceptual Modeling (pp. 249-258). Cham: Springer Nature Switzerland.
Li, Z., & Ning, H. (2023). Autonomous GIS: the next-generation AI-powered GIS. arXiv preprint arXiv:2305.06453.
Routing with Disruption:
Chen, C. C., Tsai, Y. H., & Schonfeld, P. (2016). Schedule coordination, delay propagation, and disruption resilience in intermodal logistics networks. Transportation Research Record, 2548(1), 16-23.
Rosyida, E. E., Santosa, B., & Pujawan, I. N. (2019, April). Combinational disruptions impact analysis in road freight transportation network. In AIP Conference Proceedings (Vol. 2097, No. 1). AIP Publishing.
Ahmady, M., & Eftekhari Yeghaneh, Y. (2022). Optimizing the cargo flows in multi-modal freight transportation network under disruptions. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 1-20.
Shen, G., & Aydin, S. G. (2014). Highway freight transportation disruptions under an extreme environmental event: the case of Hurricane Katrina. International Journal of Environmental Science and Technology, 11, 2387-2402.
Others: