Special Session Chairs

Dr Shengxiang Yang
Dept. of Computer Science
University of Leicester, UK
Dr Hans-Georg Beyer
Dept. of Computer Science
Vorarlberg University of Applied Sciences, Austria
Dr Yaochu Jin
Honda Research Institute Europe, Germany
Dr Ponnuthurai N. Suganthan
School of Electrical & Electronic Engineering
Nanyang Tech. University, Singapore
Program Committee

Hussein A. Abbass (Australia)

Dirk Arnold (Canada)

Thomas Bartz-Beielstein (Germany)

Tim Blackwell (UK)

Peter A. N. Bosman (The Netherlands)

Juergen Branke (Germany)

Hui Cheng (UK)

Ernesto Costa (Portugal)

Kalyanmoy Deb (India)

Andries P. Engelbrecht (South Africa)

Chi-Keong Goh (Singapore)

Xiaodong Li (Australia)

Ronald Morrison (USA)

Ferrante Neri (Finland)

Yew Soon Ong (Singapore)

William Rand (USA)

Khaled Rasheed (USA)

Hendrik Richter (Germany)

Philipp Rohlfshagen (UK)

Kay Chen Tan (Singapore)

Renato Tinos (Brazil)

Sima Uyar (Turkey)

Karsten Weicker (Germany)

Qingfu Zhang (UK)

Important Dates

 Submission Deadline:

              Nov 1, 2008

Author Notification:

             Jan 16, 2009

Camera-ready Papers:

            Feb 16, 2009 



Call for Papers
  Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE'09)
May 18 - 21, 2009, Trondheim, Norway


Many real-world optimization problems are subjected to dynamic and uncertain environments that are often impossible to avoid in practice. For instance, the fitness function is uncertain or noisy as a result of simulation/measurement errors or approximation errors (in the case where surrogates are used in place of the computationally expensive high fidelity fitness function). In addition, the design variables or environmental conditions may also perturb or change over time. For these dynamic and uncertain optimization problems, the objective of the evolutionary algorithm is no longer to simply locate the global optimum solution, but to continuously track the optimum in dynamic environments, or to find a robust solution that operates optimally in the presence of uncertainties. This poses serious challenges to conventional evolutionary algorithms.  

Handling dynamic and uncertain optimization problems in evolutionary computation has received an increasing research interests over the recent years. A variety of methods have been reported across a broad range of application backgrounds. This special session aims at bringing researchers from academia and industry together to review the latest advances and explore future directions in this field. Topics of interest include but are not limited to:

  • Benchmark problems and performance measures
  • Tracking moving optima
  • Dynamic multi-objective optimization
  • Adaptation, learning, and anticipation
  • Handling noisy fitness functions
  • Using fitness approximations
  • Searching for robust optimal solutions
  • Comparative studies
  • Hybrid approaches
  • Theoretical analysis
  • Real-world applications 

Paper Submission: Manuscripts should be prepared according to the standard format and page limit of regular papers specified in CEC2009 and submitted through the website http://www.cec-2009.org/submission.shtml. Special session papers will be treated in the same way as regular papers and included in the conference proceedings.

Authors are encouraged to participate in the CEC2009 competition on EC in Dynamic and Uncertain Environments associated with the special session. Accepted papers that involve Memetic Computing are also encouraged to be extended for submission to the Thematic Issue on Memetic Computing in the Presence of Uncertainties for the journal of Memetic Computing, Springer.