You're sincerely invited to submit your paper to a special session* "AI-driven
last-mile logistics"* of the upcoming IEEE ITSC-2023 (24-28 September,
2023) in Bilbao, Bizkaia, Spain.
Please find more detailed information below if you're interested.
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PLEASE SUBMIT YOUR INVITED CONTRIBUTION AT
https://its.papercept.net/conferences/scripts/submissionwizard.pl?ConfID=81
SUBMIT AS *Special Session Paper* (deadline *May 15, 2023*) USING THE
5-CHARACTER CODE* 65h2n*
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Conference: 2023 26th IEEE International Conference on Intelligent
Transportation Systems Submission number: 56
Special Session: *"AI-driven last-mile logistics"*
In this special session, we focus on both classical and emerging AI methods
for last-mile logistics. Decision makers often have to make decisions in an
uncertain environment and confront conflicting goals, for example,
improving efficiency (and customer service level) versus reducing
costs/emissions. In addition, lack of robustness of system-generated
solutions would discourage decision makers to apply these solutions in real
world cases.
To provide executable and understandable solutions in real-world
decision-making environment, we encourage and expect to produce high
quality research in traffic disruption forecasting, vehicle routing in an
uncertain environment and a combination of forecasting and planning.
Interesting topics include but not limited to traffic disruption
forecasting and anomaly detection based on historical and real-time
monitoring data, multi-objective optimization, robust optimization,
stochastic optimization, simulation-based methods, learning-based methods,
and explainable artificial intelligence methods in last-mile logistics.
o Topics of interest for the special session
This session aims to gather researchers in the field of artificial
intelligence in last-mile logistics. Interesting topics include but not
limited to
• multi-objective optimization for last-mile delivery
• hyperparameter optimization for last-mile logistics
• learning-based methods for vehicle routing problems
• stochastic/robust optimization in last-mile logistics in an
uncertain environment
• data-driven modeling/optimization for on-demand delivery
• approximate dynamic programming for vehicle routing problems
• explainable artificial intelligence in last-mile logistics
• predictive online optimization for on-demand delivery
• online vehicle routing in crowdsourced delivery
• behavioral operations research in attended home delivery
Kind Regards,
*Dr. Yingjie Fan*
Assistant Professor
E-mail address: y.fan@liacs.leidenuniv.nl
*Prof. Dr. Thomas Bäck*
Head Natural Computing Group
T.H.W.Baeck@liacs.leidenuniv.nl
*Universiteit Leiden* | Faculteit der Wiskunde en Natuurwetenschappen -
LIACS | www.universiteitleiden.nl
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