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ORGANIZER;CN=Michael McDonald:mailto:michael.mcdonald@fsu.edu
DESCRIPTION;LANGUAGE=en-US:"Bi-level Optimization for Multi-Period Charging
  Infrastructure Planning in Waste Collection"\n\nYanshuo Sun\nIndustrial E
 ngineering\,\nFlorida A&M University-Florida State University (FAMU-FSU) C
 ollege of Engineering\n\nPlease feel free to forward/share this invitation
  with other groups/disciplines that might be interested in this talk/topic
 . All are welcome to attend.\n\nNOTE: In-person attendance is requested in
  our 499 Dirac Science Library (DSL) Seminar Room. Zoom access is intended
  for external (non-departmental) participants only.\n\nhttps://fsu.zoom.us
 /j/94273595552\nMeeting # 942 7359 5552\n\n\nWednesday\, Oct 14\, 2026\, S
 chedule:\n\n  *\n3:00 to 3:30 PM Eastern Time (US and Canada)\n     *\n☕
  Nespresso & Teatime - 417 DSL Commons\n\n  *\n3:30 to 4:30 PM Eastern Tim
 e (US and Canada)\n     *\n🕟 Colloquium - 499 DSL Seminar Room\n\nAbstr
 act:\nThe planning of charging infrastructure over time is crucial to addr
 ess the growing need for electric vehicles. The problem is characterized b
 y the interaction between the decisions of infrastructure planners and use
 rs at two levels. Despite the extensive adoption of bilevel programming mo
 dels to capture this complex interaction\, existing models typically addre
 ss the problem within a single planning period. To address this gap\, we p
 resent the first multi-period bilevel optimization model for charging infr
 astructure planning\, with an application to solid waste collection\, and 
 develop two solution algorithms: a decomposition-based approach for solvin
 g 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 appr
 oach decomposes the routing and charging decisions into two separate probl
 ems 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-specifi
 c dominance rules that evaluates only the necessary DP states. Computation
 al tests show that the decomposition-based approach reduces computation ti
 me 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 show
 s that the labeling approach achieves the same solution as the brute-force
  approach while evaluating 99.9% fewer planning paths. The proposed soluti
 on approaches can be adopted by municipalities to address the charging inf
 rastructure planning problem for their electrified SWC operations.\n\n\nAd
 ditional colloquium details can be found here:\nhttps://www.sc.fsu.edu/new
 s-and-events/colloquium/colloquium-with-yanshuo-sun-2026-10-14<https://nam
 04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sc.fsu.edu%2Fne
 ws-and-events%2Fcolloquium%2Fcolloquium-with-yanshuo-sun-2026-10-14&data=0
 5%7C02%7Csc-seminar-announce%40lists.fsu.edu%7C607c1308bb634b5a1e2f08df27d
 b4596%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639273494849449634%7CUn
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 fK5GRG%2FJg1JY4BoL1r01CWFzkvE%3D&reserved=0>\n\n🎦 Colloquium recordings
  will be made available here:\nhttps://www.sc.fsu.edu/news-and-events/semi
 nars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww
 .sc.fsu.edu%2Fnews-and-events%2Fseminars&data=05%7C02%7Csc-seminar-announc
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SUMMARY;LANGUAGE=en-US:Scientific Computing Colloquium with Yanshuo Sun
DTSTART;TZID=Eastern Standard Time:20261014T153000
DTEND;TZID=Eastern Standard Time:20261014T162500
CLASS:PUBLIC
PRIORITY:5
DTSTAMP:20261011T210442Z
TRANSP:OPAQUE
STATUS:CONFIRMED
SEQUENCE:1
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