A special issue of International Journal of Bio-Inspired Computation
Differential evolution (DE) is a method of mathematical optimization of multi- dimensional functions and belongs to the class of evolution strategy optimizers. DE finds the global minimum of a multidimensional, multimodal (i.e. exhibiting more than one minimum) function with good probability. The crucial idea behind DE is a scheme for generating trial parameter vectors. DE adds the weighted difference between two population vectors to a third vector. In this way, no separate probability distribution has to be used, which makes the scheme completely self-organizing.
The objective of this special issue is to bring researchers from academia and industry together to report and review the latest progresses in this field, and to explore future directions.
Relevant topics include, but are not limited to, the following:
- Theoretical advances in differential evolution methodology
- Differential evolution n for complex constrained optimisation problems
- Differential evolution for multi-objective optimisation problems
- Differential evolution for dynamic environment optimisation
- Hybrid methods combined with other optimisation techniques
- Learning and search strategies in differential evolution
- Applications of differential evolution, such as bio-informatics and chem-informatics, computational biology, etc.
- Future directions of differential evolution
Submission Deadline: 1 November, 2008
Acceptance Notification: 1 February,2009
Final Manuscript Submission: 1 March,2009