Aim and Scope

Surrogate-assisted evolutionary optimization of computationally expensive problems is an area of research that has grown rapidly in recent years. The motivation for this interest is that constructing a surrogate model to approximate an expensive function can substantially reduce the computational cost for fitness evaluations in evolutionary optimization and improve the optimization search performance. This is of significant importance, as in many real-world problems fitness evaluations are computationally expensive.

The aim of this special session is to bring together researchers from different application fields working on evolutionary optimizations assisted by surrogate models. The main focus is to review and discuss about the state of the art in the theory and practice of using surrogate-assisted evolutionary computation for computationally expensive real-world problems, including engineering design, qualitative optimizations with interactive evolutionary computation, and chemical process optimizations, to name a few. Interested topics include but are not limited to:

• Surrogate-assisted evolutionary optimization of complex engineering problems
• Surrogate models for computationally expensive simulations
• Evolutionary multi-objective optimizations with surrogate models
  
• Surrogate model-assisted interactive evolutionary optimizations
  
• Surrogate-assisted robust optimization
  
• Surrogates for dealing with uncertainties and constrains in optimization
  
• Function approximation-based and simulation-based surrogate models
  
• Classification-assisted evolutionary optimization
  
• Trust region methodologies for surrogate-assisted evolutionary optimization
  
• Supervised, semi-supervised and incremental learning for evolutionary optimization
  
• Fidelity analysis and surrogate management

Paper Submission

Special session papers should be submitted electronically through the IEEE WCCI 2012 main website. Please indicate during submission that your paper is submitted to this special session.

Organizers

• Xiaoyan Sun
  School of Information and Electrical Engineering, China University of Mining and Technology, China
  Email: xiaoyan.sun@surrey.ac.uk, xysun78@126.com
  
  
• Yew Soon Ong
  Center for Computational Intelligence, Nanyang Technological University, Singapore
  Email: asysong@ntu.edu.sg
  
  
• Yaochu Jin
  Department of Computing, University of Surrey, UK
  Email: yaochu.jin@surrey.ac.uk

Program Committee (confirmed)

• Christian Blum
  Universitat Politècnica de Catalunya, Spain
• Juergen Branke
  The University of Warwick
• Huanhuan Chen
  University of Birmingham, UK
• Carlos A. Coello Coello
  CINVESTAV-IPN, Mexico
• Richard Everson
  University Exeter, UK
• Jonathan Fieldsend
  University Exeter, UK
• Dunwei Gong
  China University of Mining and Technology, China
• Lars Graening
  Honda Research Institute Europe, Germany
• Haibo He
  University of Rhode Island, USA
• Yaochu Jin
  University of Surrey, UK
• Goh Chi Keong
  Rolls-Royce Singapore Pte. Ltd, Singapore
• Khaled M Rasheed
  The University of Georgia, USA
• Bin Li
  University of Science and Technology of China, China
• Roman Neruda
  Academy of Sciences of the Czech Republic, Czech Republic
• Yew Soon Ong
  Nanyang Technological University, Singapore
• Marc Schoenauer
  INRIA, France
• Chris Smith
  University of Surrey, UK
• Xiaoyan Sun
  China University of Mining and Technology, China
• Hideyuki Takagi
  Kyushu Institute of Design, Japan
• Kay Chen Tan
  National University of Singapore, Singapore
• Ke Tang
  University of Science and Technology of China
• Ling Wang
  Tsinghua University, China
• Chong Siang Yew
  University of Nottingham, Malaysia
• Qingfu Zhang
  University of Essex, UK
• Dong Zhao
  University of Calgary, Canada