Call for Papers

IEEE Transactions on Evolutionary Computation

Special Issue on

Evolutionary Optimization in Presence of Uncertainties

 

A wide range of uncertainties has to be considered in solving many real-world optimization problems. Generally, uncertainties in evolutionary optimization can be categorized into three classes.

 

1.        The fitness function is uncertain or noisy. Noise in fitness evaluations may result from many different sources such as sensory measurement errors or numerical instabilities in simulation. Uncertainties also arise when the fitness function has to be estimated, e.g., if approximate models are used or fitness inheritance is adopted in order to save costly fitness evaluations.

 

2.        The design variables or the environmental parameters are subject to perturbations 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.

 

 

3.        The fitness function is time-variant. 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.

 

Handling uncertainties in evolutionary optimization is receiving an increasing interest in the evolutionary computation community. A variety of methods for addressing uncertainties have been reported from different application backgrounds. The objective of this special issue is to collect a set of high-quality papers to discuss the above issues within a uniform framework, to reflect the most recent advances in the field and to present sophisticated real-world applications.

 

Topics of interest may include but are not limited to:

 

         handling noisy fitness functions

         handling approximation errors in fitness evaluations

         searching for robust optimal solutions

         tracking moving optima

         sophisticated real-world applications

 

Manuscripts should be prepared following the format standards of the IEEE available at http://www.ieee.org/organizations/pubs/transactions/information.htm. All submissions will be peer reviewed subject to the standards of the IEEE Transactions on Evolutionary Computation. Manuscripts based on previously published conference papers must be extended substantially. Electronic submissions in postscript or PDF are strongly preferred. If the submission is sent by regular mail, authors are requested to send six (6) copies of their manuscript. Please send all submissions to one of the guest editors:

 

Dr. Yaochu Jin Dr. Juergen Branke

Honda Research Institute Europe Institute AIFB

Carl-Legien-Str 30 University of Karlsruhe

63073 Offenbach am Main 76128 Karlsruhe,

GERMANY GERMANY

Phone: +49 69 890 11 735 Phone: +49 721 608 6585

Fax: +49 69 890 11 749 Fax : +49 721 693 717

Email: yaochu.jin@honda-ri.de Email: branke@aifb.uni-karlsruhe.de

 

A tentative schedule is as follows:

 

         Submission deadline: May 31, 2004

         Notification of acceptance: September 30, 2004

         Final manuscript: November 30, 2004