[Eoas-seminar] [Seminar-announce] Scientific Computing Colloquium with Yanshuo Sun

[eoas-seminar at lists.fsu.edu]

"Bi-level Optimization for Multi-Period Charging Infrastructure Planning in Waste Collection"

Yanshuo Sun
Industrial Engineering,
Florida A&M University-Florida State University (FAMU-FSU) College of Engineering

Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic. All are welcome to attend.

NOTE: In-person attendance is requested in our 499 Dirac Science Library (DSL) Seminar Room. Zoom access is intended for external (non-departmental) participants only.

https://fsu.zoom.us/j/94273595552
Meeting # 942 7359 5552


Wednesday, Oct 14, 2026, Schedule:

  *
3:00 to 3:30 PM Eastern Time (US and Canada)
     *
☕ Nespresso & Teatime - 417 DSL Commons

  *
3:30 to 4:30 PM Eastern Time (US and Canada)
     *
🕟 Colloquium - 499 DSL Seminar Room

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.


Additional colloquium details can be found here:
https://www.sc.fsu.edu/news-and-events/colloquium/colloquium-with-yanshuo-sun-2026-10-14<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fcolloquium%2Fcolloquium-with-yanshuo-sun-2026-10-14&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7C607c1308bb634b5a1e2f08df27db4596%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639273494849449634%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=NgACpJ65sywo3itVfK5GRG%2FJg1JY4BoL1r01CWFzkvE%3D&reserved=0>

🎦 Colloquium recordings will be made available here:
https://www.sc.fsu.edu/news-and-events/seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fnews-and-events%2Fseminars&data=05%7C02%7Csc-seminar-announce%40lists.fsu.edu%7C607c1308bb634b5a1e2f08df27db4596%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639273494849520199%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=l7%2FgMFyy%2FNKw4Mr%2BTZqxhW6Ih%2FPwhPQQoFxkXYS%2FY%2Fg%3D&reserved=0>

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