SS02: Algorithm Development of Hybrid Evolutionary Algorithms(ISICA 2017 Special Session)
Most optimization problems in engineering and science involve decision making activities. These scenarios arise due to some physical limitations or functional requirements to satisfy. Traditionally different methodologies have been developed in the realm of mathematics to solve optimization problems with their associated merits and limitations. With modern technological advancements from last two decades, the solution of optimization problems are sought by means of Evolutionary Algorithms (EAs) which are proved to be very effective. The research is also greatly influenced by combining different optimization techniques also known as hybrid technique, to alleviate the drawback of individual technique. In this respect, the immense number of research outcomes reported in the literature.
Scope
Potential topics of this invited session include, but are not limited to:
- Hybrid evolutionary-classical approaches
- Hybrid local-global search methodologies
- Hybrid multi- and many-objective optimization methodologies and decision-making
- Handling of integer, discrete and mixed variables in addition to continuous variables using hybrid techniques
- New constraint handling mechanisms using hybrid CI techniques
- Parameter adaptation in hybrid optimization
- Handling of multi-modality and uncertainty using hybrid techniques
- Hybrid meta-modeling based CI methodologies
- Hybrid dynamic optimization methodologies
- Hybrid bi-level optimization methodologies
- Complexity and efficiency using in hybrid methodology
- Algorithm linking and unification of hybrid CI approaches
- Applications of hybrid techniques in real-world problems
- Any other relevant topic
Organizers
Hui Li
Xidian University, China, hli@xidian.edu.cn