"Bi-level Optimization for Multi-Period Charging Infrastructure Planning in Waste Collection"
Wednesday, Oct 14, 2026 
- Colloquium - 499 DSL Seminar Room
- 03:30 to 04:30 PM Eastern Time (US and Canada)
Click Here to Join via Zoom
Meeting # 942 7359 5552
Zoom Meeting # 942 7359 5552
Abstract:
The planning of charging infrastructure over time is crucial to address the growing need for electric vehicles. The problem is characterized by the interaction between the decisions of infrastructure planners and users at two levels. Despite the extensive adoption of bilevel programming models to capture this complex interaction, existing models typically address the problem within a single planning period. To address this gap, we present the first multi-period bilevel optimization model for charging infrastructure planning, with an application to solid waste collection, and develop two solution algorithms: a decomposition-based approach for solving the electric vehicle routing problem (EVRP) at the lower level, and an exact dynamic programming (DP) algorithm for solving the charging station location problem at the upper level. The proposed decomposition-based approach decomposes the routing and charging decisions into two separate problems and follows a routing-first-charging-second strategy to strike a more preferable trade-off between solution quality and computation time. The DP algorithm is implemented through a labeling approach with problem-specific dominance rules that evaluates only the necessary DP states. Computational tests show that the decomposition-based approach reduces computation time by 99.8% on average relative to a commercial solver, while maintaining an average optimality gap below 1.5%. The real-world case study also shows that the labeling approach achieves the same solution as the brute-force approach while evaluating 99.9% fewer planning paths. The proposed solution approaches can be adopted by municipalities to address the charging infrastructure planning problem for their electrified SWC operations.
Speaker Biography:
Dr. Yanshuo Sun is an Associate Professor of Industrial Engineering at the Florida A&M University-Florida State University (FAMU-FSU) College of Engineering in Tallahassee, FL. He specializes in mathematical programming and big data analytics with applications in multi-modal transportation systems and logistics. He has published more than 40 papers in leading journals in his research field including IISE Transactions, Transportation Science, Transportation Research Parts A, B, C, and E. At present, he serves as the principal investigator (PI) on one project funded by the National Science Foundation (NSF) and another project funded by the Florida Department of Transportation (FDOT). He also directs a three-million-dollar research center titled Advancing Community-Centric Transportation Systems (ACTS), which is funded by the U.S. Department of Transportation (USDOT). He is a Co-PI on multiple other federal and state-funded research projects on different topics ranging from development of a composite index for transportation systems to data-driven management of Harmful Algal Blooms. He holds a Ph.D. in transportation engineering from the University of Maryland.
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 Two Figures.docx | Research Image | 689 kB |
