Tuesday, 16 October 2018

CFP: IEEE CEC 2019 Special Session on Data-Driven Evolutionary Optimization of Computationally Expensive Problems

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 issue 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 multi-disciplinary optimization.

Important Dates

Submission deadline:7 January 2019
Notification: 7 March 2019
Final paper submission: 31 March 2019
Early Registration: 31 March 2019


The papers must be submitted online through the manuscript submission system (http://cec2019.org/papers.html#submission). 


Prof. Chaoli Sun, Department of Computer Science and Technology, Taiywan University of Science and Technology, China. 

Prof. Jonathan Fieldsend, Department of Computer Science, University of Exeter, United Kingdom. 

Prof. Yew-Soon Ong, School of Computer Engenieering, Nanyang Technological University, Singapore. 

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