Workshop Homepage and Announcement

"Evolutionary Algorithms for Dynamic Optimization Problems"

a bi-annual Workshop which is part of

The 2005 Genetic and Evolutionary Computation Conference (GECCO-2005)

26 June, 2005
Washington D. C., USA

Check the Call for Papers for the Genetic Programming and Evolvable Machines special issue on "EC in Dynamic and Uncertain Environments". Papers accepted for the workshop will be judged as to whether an extended version would be suitable for the special issue. All authors of papers deemed appropriate are encouraged to submit an extended version to the journal, and will undergo a fast track reviewing process.


Many real-world optimization problems are actually dynamic. New jobs are to be added to the schedule, the quality of the raw material may be changing, new orders have to be included into the vehicle routing problem etc.

In such cases, when the problem changes over the course of the optimization, the purpose of the optimization algorithm changes from finding an optimal solution to being able to continuously track the movement of the optimum through time. Since in a sense natural evolution is a process of continuous adaptation, it seems straightforward to consider evolutionary algorithms as appropriate candidates for dynamic optimization problems.

And indeed, the number of papers published in that area is rising continuously (see e.g. the online repository on the topic). Most of these publications can be grouped into one of the following basic categories:

  1. Identify the occourence of a change in the environment and then deliberately increase diversity in the population e.g. by means of increased mutation
  2. Try to avoid convergence all the time, e.g. by including new random individuals in the population in every generation
  3. Supply the EA with a memory, e.g. by using diploidy or an explicit memory, so that the EA can recall useful information from past generations.
  4. Using multiple populations to cover several promising areas of the search space simultaneously.

The goal of the workshop will be to foster interest in the subject, get together researchers working on that topic, and achieve an informal agreement on some of the key issues in the field.

A similar workshop has been held at GECCO-1999, GECCO-2001, and GECCO-2003 with 60-100 participants each. Now, another two years later, it seems to be time for an update.

Workshop Schedule

8:30Shengxiang Yang and Jürgen Branke. EvoDOP-2005 Workshop Introduction
8:35Abdunnaser Younes, Paul Calamai, and Otman Basir. Generalized Benchmark Generation for Dynamic Combinatorial Problems
9:00William Rand and Rick Riolo. Measurements for Understanding the Behavior of the Genetic Algorithm in Dynamic Environments: A Case Study Using the Shaky Ladder Hyperplane-Defined Functions
9:25Peter A.N. Bosman. Learning, Anticipation and Time-Deception in Evolutionary Online Dynamic Optimization
10:05Amine Boumaza. Learning Environment Dynamics from Self-Adaptation
10:30Dudy Lim, Yew-Soon Ong, Bu-Sung Lee. Inverse Multi-Objective Robust Evolutionary Design Optimization in the Presence of Uncertainty
10:55Yaochu Jin, Markus Olhofer, and Bernhard Sendhoff. Finding the Optimal Search Dimension for Evolution Strategies with a Small Population
11:35Open discussion on topics listed below
12:30End of the workshop

The workshop is open to all registered attendees of the GECCO-2005 conference. We are open for topics that should be discussed during the panel discussion. Here are some preliminary ideas:

Workshop Chairs:

Dr. Shengxiang Yang 
Department of Computer Science
University of Leicester 
University Road
Leicester LE1 7RH, United Kingdom 
Tel: +44-116-252 5341
Fax: +44-116-252 3915 

Dr. Jürgen Branke
Institute AIFB
University of Karlsruhe 
76128 Karlsruhe, Germany 
Tel: +49-721-608 6585
Fax: +49-721-693717 

Program Committee:

Ernesto Costa (Portugal)
Kenneth DeJong (USA)
Ron Morrison (USA)
Karsten Weicker (Germany)
Tim Blackwell (UK)
Sima Uyar (Turkey)
William Rand (USA)
Hussein A. Abbass (Australia)
Daniel Merkle (Germany)