Speaker: Handing Wang, Xidian University, China
Date: 17 March 2025
Time: 4:00 - 5:00pm (Beijing Time, UTC+8)
Handing Wang received the B.Eng. and Ph.D. degrees from Xidian University, Xi'an, China, in 2010 and 2015, respectively. She is currently a professor with School of Artificial Intelligence, Xidian University, Xi'an, China. Dr. Wang is an Associate Editor of IEEE Transactions on Evolutionary Computation, Swarm and Evolutionary Computation, and Complex \& Intelligent Systems. Her research interests include nature-inspired computation, multiobjective optimization, surrogate-assisted evolutionary optimization, Trustworthy AI, and real-world problems.
Many real-world combinatorial optimization problems have no analytic objective functions are available but use expensive simulations for evaluating candidate solutions. Surrogate-assisted optimization methods, which build models to approximate both objective and constraint functions, are common solutions for expensive combinatorial optimization problems. However, challenges raise in surrogate model building and search in discrete space. In this webinar, some possible methods to address those issues will be discussed.
The Webinar went very successful, with 50+ participants.
The video recording of the Webinar can be found here.
The slides of the Webinar can be found here.
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