2017 IEEE Symposium Series on Computational Intelligence (SSCI 2017), November 27-December 1, 2017, Hawaii, USA
Call for Papers
2017
IEEE Symposium on Model Based Evolutionary Algorithms (IEEE MBEA'17)
in Hawaii, USA.
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Special Session on
Data-Driven
Evolutionary Optimization of Computationally Expensive Problems
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Summary of the special session:
Meta-heuristic algorithms, including evolutionary algorithms and swarm
optimization, face challenges when solving time-consuming problems, as
typically these approaches require thousands of function evaluations to arrive
at solutions that are of reasonable quality. Surrogate models, which are
computationally cheap, have in recent years gained in popularity in assisting
meta-heuristic optimization, by replacing the compute-expense/time-expensive problem
during phases of the heuristic search. However, due to the curse of dimensionality, it is very difficult, if not
impossible to train accurate surrogate models. Thus, appropriate model
management techniques, memetic strategies and other schemes are often
indispensable. In addition, modern data analytics involving advance sampling
techniques and learning techniques such as semi-supervised learning, transfer
learning and active learning are highly beneficial for speeding up evolutionary
search while bringing new insights into the problems of interest. This
special session aims at bringing together researchers from both academia and
industry to explore future directions in this field.
Scope and Topics:
The
topics of this special session include but are not limited to the following
topics:
- Surrogate-assisted evolutionary optimization for computationally expensive
problems
- Adaptive sampling using machine learning and statistical techniques
- Surrogate model management in evolutionary optimization
- Data-driven optimization using big data and data analytics
- Knowledge acquisition from data and reuse for evolutionary optimization
- Computationally efficient evolutionary algorithms for large scale and/or
many-objective optimization problems
- Real world applications including multidisciplinary
optimization
Important
Dates:
-
Paper submission
: July 2, 2017
- Notification to authors : August 27, 2017
- Final submission : September 24, 2017
- Early registration : September 24, 2017
Organizers:
Chaoli Sun, Department of Computer Science and Technology, Taiyuan University of Science and Technology, China
Jonathan Fieldsend, Department of Computer Science, University of Exeter,
UK
Yew-Soon Ong, School of Computer Engineering, Nanyang Technological University,
Singapore