Evolutionary Computation in Dynamic and Uncertain Environments

The primary target of the task Force is to promote research on evolutionary computation in dynamic and uncertain environments. This is an emerging area in evolutionary computation, which covers the following different but closely related topics:

Evolutionary computation (optimization) with noisy fitness evaluations. Noise in fitness evaluations may result from many different sources such as sensory measurement errors or numerical instabilities in simulation. Basic strategies to handle noisy fitness functions include population sizing, averaging by re-sampling, or changing the selection criteria.
Evolutionary computation (optimization) with approximate or imprecise fitness (quality) evaluations. The primary motivation to use computationally efficient but imprecise fitness evaluations is that the original fitness function is too expensive or does not exist. In comparison to noisy fitness functions, uncertainties introduced by approximate fitness evaluations are biased and cannot be reduced by re-sampling the approximate fitness function. The most popular method to obtain computationally efficient fitness evaluations is to construct a meta-model (surrogate) based on available data. Ad hoc methods such as fitness inheritance, fitness imitation or fitness assignment can also be employed.
Evolutionary optimization where the design variables or the environmental parameters are subject to stochastic or deterministic changes. It is very common that a system to be optimized is expected to perform satisfactorily even when the design variables or the environmental parameters change within a certain range, or the system has to work on more than one pre-determined nominal point. This issue is often known as the search for robust optimal solutions.
Evolutionary computation with a time-varying fitness function. In other words, the optimum of the system is changing with time, which requires a repeated re-optimization or even continuous tracking of the optimum. As a matter of fact, in multi-objective evolutionary computation and co-evolutionary systems, the fitness landscape changes over time.

Benchmark Test Problems

The benchmark problems and technical report for the CEC'09 Competition on Evolutionary Computation in Dynamic and Uncertain Environments.
Yang's XOR DOP generator in C.
Branke's Moving Peaks Benchmark (MPB) problem.
Morrison and De Jong's Dynamic Test Function Generator (DF-1).
Benchmark data sets for Dynamic Vehicle Routing Problems.

Books and Journal Special Issues

S. Yang and X. Yao (editors), Evolutionary Computation for Dynamic Optimization Problems, in the book series Studies in Computational Intelligence, Springer-Verlag Berlin Heidelberg, expected in 2012.
S. Yang, Y.-S. Ong, and Y. Jin (editors), Evolutionary Computation in Dynamic and Uncertain Environments, in the book series Studies in Computational Intelligence, vol. 51, Springer-Verlag Berlin Heidelberg, 2007.
W. Weicker (author), Evolutionary Algorithms abd Dynamic Optimization Problems, Berlin, Germany: Der Andere Verlag, 2003.
R. W. Morrison (author), Designing Evolutionary Algorithms for Dynamic Environments, Springer-Verlag, 2004.
J. Branke (author), Evolutionary Optimization in Dynamic Environments, Kluwer Academic Publishers, 2002.
C.-K. Goh and F. Neri (guest-editors), Special Issue on Computational Intelligence in the Presence of Uncertainties, International Journal of Systems Science, Taylor and Francis, in preparation.
F. Neri and S. Yang (guest-editors), Thematic Issue on Memetic Computing in the Presence of Uncertainties, Memetic Computing, vol. 2, no. 2, June 2010.
S. Yang, Y.-S. Ong, and Y. Jin (guest-editors), Special Issue on Evolutionary Computation in Dynamic and Uncertain Environments, Genetic Programming and Evolvable Machines, vol. 7, no. 4, December 2006.
Y. Jin and J. Branke (guest-editors), Special Issue on Evolutionary Optimization in the Presence of Uncertainties, IEEE Transactions on Evolutionary Computation, vol. 10, no. 4, August 2006.
J. Branke (guest-editor), Special Issue on Dynamic Optimization Problems, Soft Computing, vol. 9, no. 11, November 2005.

Organized Competitions

C. Li, S. Yang, and D. A. Pelta (co-chairs), Competition on Evolutionary Computation for Dynamic Optimization Problems, part of WCCI-2012 Competitions, Brisbane, Australia, 10-15 June, 2012.
S. Yang, H.-G. Beyer, Y. Jin, and P. N. Suganthan (co-chairs), Competition on Evolutionary Computation in Dynamic and Uncertain Environments, part of CEC-2009 Competitions, Trondheim, Norway, 18-21 May, 2009.

Organized Symposium, Workshops, and Special Sessions

Y. Jin, S. Yang, and R. Polikar (co-chairs), IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE 2013), part of the 2013 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2013), Singapore, 16-19 April, 2013.
D. A. Pelta, S. Yang, Y. Jin, and C. Li (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE12), part of the 2012 IEEE World Congress on Computational Intelligence (IEEE WCCI 2012), Brisbane, Australia, 10-15 June, 2012.
Y. Jin, S. Yang, and R. Polikar (co-chairs), IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE 2011), part of the 2011 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2011), Halle aux Farines, Paris, France, 11-15 April, 2011.
S. Yang, D. A. Pelta, and Y. Jin (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE11), part of the 2011 IEEE Congress on Evolutionary Computation (IEEE CEC 2011), New Orleans, USA, 5-8 June, 2011.
D. A. Pelta, S. Yang, and Y. Jin (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE10), part of the 2010 IEEE World Congress on Computational Intelligence (IEEE WCCI 2010), Barcelona, Spain, 18-23 July, 2010.
S. Yang, H.-G. Beyer, Y. Jin, and P. N. Suganthan (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE09), part of the 2009 IEEE Congress on Evolutionary Computation (IEEE CEC 2009), Trondheim, Norway, 18-21 May, 2009.
C.-K. Goh, A. P. Engelbrecht, S. Yang, and K. C. Tan (co-chairs), Special Session on Evolutionary Computation in Uncertain Environments (ECiDUE08), part of the 2008 IEEE World Congress on Computational Intelligence (IEEE WCCI 2008), Hong Kong, 1-6 June, 2008.
A. P. Engelbrecht, S. Yang, and Y. Jin (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE07), part of the 2007 IEEE Congress on Evolutionary Computation (IEEE CEC 2007), Singapore, 25-28 September, 2007.
S. Yang and Y. Jin (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE06), part of the 2006 IEEE World Congress on Computational Intelligence (IEEE WCCI 2006), Vancouver, Canada, 16-21 July, 2006.
S. Yang and Y.-S. Ong (co-chairs), Special Session on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE05), part of the 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005), Edinburgh, UK, 2-5 September, 2005.
S. Yang and J. Branke (co-chairs), Special Session on Evolutionary Optimization in Dynamic Environments (EODE04), part of the 2004 IEEE Congress on Evolutionary Computation (IEEE CEC 2004), Portland, USA, 19-23 June 2004.
F. Neri and H. Richter (co-chairs), the 8th European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2011), part of Evo* 2011, Torino, Italy, 27-29 April, 2011.
F. Neri and C.-K. Goh (co-chairs), the 7th European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2010), part of Evo* 2010, Istanbul, Turkey, 7-9 April, 2010.
S. Yang and F. Neri (co-chairs), the 6th European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2009), part of Evo* 2009, Tübingen, Germany, 15-17 April, 2009.
S. Uyar and S. Yang (co-chairs), the 5th European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSTOC2008), part of Evo* 2008, Napoli, Italy, 26-28 March, 2008.
S. Uyar and S. Yang (co-chairs), the 4th European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2007), part of Evo* 2007, Valencia, Spain, 11-13 April, 2007.
J. Branke and E. Costa (co-chairs), the 3rd European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2006), part of Evo* 2006, Budapest, Hungary, 10-12 April, 2006
J. Branke and Y. Jin (co-chairs), the 2nd European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2005), part of Evo* 2005, Lausanne, Switzerland, March 30-April 1, 2005
J. Branke and Y. Jin (co-chairs), the 1st European Workshop on Evolutionary Algorithms in Stochastic and Dynamic Environments (EvoSOTC2004), part of Evo* 2004, Coimbra, Portugal, 5-7 April 2004.
P. A. N. Bosman and J. Branke (co-chairs), the 5th Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, part of GECCO-2007, London, UK, 7-11 July, 2007.
S. Yang and J. Branke (co-chairs), the 4th Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, part of GECCO-2005, Washington DC, USA, 25-29 June, 2005.
J. Branke (chair), the 3rd Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, part of GECCO-2003, Chicago, USA, 12-16 July, 2003.
J. Branke and T. Baeck (co-chairs), The 2nd Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, part of GECCO-2001, San Francisco, USA, 7-11 July, 2001.
J. Branke and T. Baeck (co-chairs), the 1st Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, part of GECCO-1999, Orlando, Florida, 13-17 July, 1999.

Relevant PhD Theses

Changhe Li, Particle Swarm Optimization in Stationary and Dynamic Environments, University of Leicester, UK, 2011.
Trung Thanh Nguyen, Continuous Bynamic Optimisation Using Evolutionary Algorithms, University of Birmingham, UK, 2010.

Resources and Relevant Links

The UK EPSRC Project on Evolutionary Algorithms for Dynamic Optimisation Problems: Design, Analysis and Applications, a joint project between University of Leicester, Brunel University, University of Birmingham, BT, and Honda.
A repository on Intelligent Strategies in Uncertain and Dynamic Environments.
A tutorial on Fitness Approximation in Evolutionary Computation by Yaochu Jin and Khaled Rasheed on GECCO'05, June 26, Washington D.C., 2005
A tutorial on Evolutionary Computation in Dynamic and Uncertain Environments by Yaochu Jin on CEC'04, Portland, USA, July 2004.
A survey paper on Evolutionary Optimization in Uncertain Environments by Yaochu Jin and Juergen Branke. Published in IEEE Transactions on Evolutionary Computation, 9(3): 303-317, 2005.
A survey paper on Fitness Approximation in Evolutionary Computation by Yaochu Jin. Published in Soft Computing, 9(1):3-12, 2005.
A bibliography on Evolutionary Computation with Approximate Fitness Functions.
A bibliography on Evolutionary Optimization in/for Noisy Environments .
A bibliography on Evolutionary Algorithms for Dynamic Optimization Problems.

Contact

Note: The copyright of the source codes and unpublished slides available on this homepage is reserved by the corresponding authors. Use all or part of the materials for any purpose other than personal use, such as lecture handouts, is allowed but should be properly acknowledged.

Last modified: . Maintained by Shengxiang Yang. Any opinions expressed on this page are those of the author.

Chair

Vice-Chairs

Membership

Target and Motivation