Special Session: Advanced Analytics and Optimization for Transportation and Logistics Decision-Making

This special session emphasizes the methodological foundations that enable these domains. It highlights advanced data analytics, artificial intelligence, simulation, and optimization frameworks that cut across multiple transport and supply chain problems. These algorithmic and model-driven studies often do not fit neatly within application-based sessions and are typically dispersed across the program. By consolidating them into one dedicated track, the session fosters deeper technical discussion, stronger knowledge exchange, and focused collaboration among researchers developing next-generation decision-support and computational tools for smart transportation and logistics systems.

This special session focuses on advanced analytical, computational, and optimization methodologies that support data-driven decision-making in transportation and logistics systems.The session highlights methodological innovations such as machine learning, simulation–optimization, metaheuristics, and multi-criteria decision models applied to complex transport and logistics problems. The session welcomes algorithmic developments, hybrid AI–optimization frameworks, predictive analytics, and decision-support tools that improve efficiency, resilience, and sustainability of transportation and supply chain systems. Both theoretical and applied studies, including graduate thesis-based research, are encouraged.

Related Topics for this Session (but not limited to):

1. Machine learning and predictive analytics for transport/logistics
2. Multi-objective and multi-criteria decision-making (AHP, TOPSIS, VIKOR, DEA, etc.)
3. Metaheuristics and evolutionary optimization (GA, PSO, ACO, DE, NSGA-II, etc.)
4. Simulation–optimization and digital twin frameworks
5. Stochastic, robust, and uncertainty modeling
6. Hybrid AI–optimization algorithms
7. Data-driven decision-support systems
8. Big data processing and real-time analytics architectures
9. Performance evaluation and benchmarking frameworks

Short Biography of Organizers

Asst. Prof. Ma. Kathleen L. Duran is a faculty member in the School of Engineering and Architecture under Civil Engineering Department at National University – Laguna, Philippines. Her research focuses on data-driven modeling, optimization, applied operation research and decision-support frameworks applied to transportation and logistics systems, sustainability education and financial engineering. She actively supervises thesis projects and serves as a technical program committee member and reviewer for international conferences and journal.

Asst. Prof. Jomar M. Llanto is a faculty member in the School of Engineering and Architecture under Civil Engineering Department and an active researcher in transportation and logistics–related engineering systems. His research interests include structural engineering and transportation systems analysis. He is actively involved in supervising student thesis projects and supporting research and innovation initiatives.

Asst. Prof. Ferly Ann R. Revilloza is a faculty member in the School of Engineering and Architecture under Civil Engineering Department at National University – Laguna, Philippines. Her academic and research interests focus on construction systems, geotechnical applications, and the integration of analytical and data-driven approaches in infrastructure-related studies. She actively supervises student thesis projects and participates in research initiatives related to transportation and civil engineering systems.

Submit Method:
1, submit it via the link: http://confsys.iconf.org/submission/ictle2026 (after entering the link, click on the corresponding topic)
2, send your manuscript to ictleconf@126.com with subject "Submit+Special Session-2+Paper Title".