Evolutionary computation has become an essential tool for solving difficult and high-dimensional optimization and classification problems in a broad range of real data management and knowledge discovery problems. Evolutionary computation is associated with systems that use computational models of evolutionary processes (i.e. based to some degree on the evolution of biological life in the natural world) as the key elements in design and implementation.
A number of evolutionary computational and related metaheuristic models have been proposed, including genetic algorithms, genetic programming, evolution strategies, evolutionary programming, learning classifier systems and other genetics-based machine learning, evolvable hardware, artificial life, adaptive behavior, ant colony optimization, swarm intelligence, etc.
Authors are invited to submit their original and unpublished work (theoretical and empirical contributions) in the areas of evolutionary and other related meta-heuristic algorithms approaches.
Suitable topics include but are not limited to:
- Distributed and parallel computation
- Representation and operators
- Adaptation and tuning of the control parameters
- Self- adaptation
- Constraints handling with EC
- Population dynamics analysis
- Fitness landscape analysis
- Hybrid algorithms
- Real-world applications
- Data mining and knowledge discovery
- Combinatorial and numerical optimization
- Very high-dimensional optimization
- Classifier systems
- Industrial and engineering applications
- Telecommunications and networks
- Scheduling and planning
- Transportation and logistics
- Dynamic and uncertain environments
- Economic and financial applications
Full paper submission: 15 November, 2010
Notification of Acceptance: 15 January, 2011
(Revise and resubmit notification; only papers with minor review requirements will be accepted)
Resubmit deadline: 30 February, 2011
No comments:
Post a Comment