Aim and ScopeDifferential evolution (DE) emerged as a simple and powerful stochastic real-parameter optimizer more than a decade ago and has now developed into one of the most promising research areas in the field of evolutionary computation. The success of DE has been ubiquitously evidenced in various problem domains, e.g., continuous, combinatorial, mixed continuous-discrete, single-objective, multi-objective, constrained, large-scale, multimodal, dynamic and uncertain optimization problems. Furthermore, the remarkable efficacy of DE in real-world applications significantly boosts its popularity.
Over the past decades, numerous studies on DE have been carried out to improve the performance of DE, to give a theoretical explanation of the behavior of DE, to apply DE and its derivatives to solve various scientific and engineering problems, as demonstrated by a huge number of research publications on DE in the forms of monographs, edited volumes and archival articles. Consequently, DE related algorithms have frequently demonstrated superior performance in challenging tasks. It is worth noting that DE has always been one of the top performers in previous competitions held at the IEEE Congress on Evolutionary Computation. Nonetheless, the lack of systematic benchmarking of the DE related algorithms in different problem domains, the existence of many open problems in DE, and the emergence of new application areas call for an in-depth investigation of DE.
This special session aims at bringing together researchers and practitioners to review and re-analyze past achievements, to report and discuss latest advances, and to explore and propose future directions in this rapidly emerging research area. Authors are invited to submit their original and unpublished work in the areas including, but not limited to:
- DE for continuous, discrete, mixed continuous-discrete, single-objective, multi-objective, constrained, large-scale, multiple optima seeking, dynamic and uncertain optimization
- Review, comparison and analysis of DE in different problem domains
- Experimental design and analysis of DE
- Studies on initialization, reproduction and selection schemes in DE
- Studies on control parameters (e.g. scale factor, crossover rate, population size) in DE
- Self-adaptive and tuning-free DE
- Parallel and distributed DE
- Theory of DE
- Synergy between DE and learning techniques
- Hybridization of DE with other optimization techniques
- Interactive DE
- Application of DE in real-world applications
Important DatesPaper submissions December 20, 2013
Notification of acceptance March 15, 2014
Please refer to: http://www.ieee-wcci2014.org/ for the latest information.
Paper SubmissionAll papers should be submitted electronically through:
When you submit your papers to our special session, please select "SS18.EC18: Differential Evolution: Past, Present and Future" as the Main research topic*.
RMIT University, Australia
Kenneth V. Price
Electronics and Communication Sciences Unit, Indian Statistical Institute, India
Department of Computer Science, University of Vaasa, Finland