SS02: Algorithm Development of Hybrid Evolutionary Algorithms(HPCA 2019 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.

Based on the above theme, the objective of this proposal is to invite researchers to address various challenging optimization problems using hybrid EAs. The scheme is to initiate discussions and deliberations peculiar to, and encompassing all related areas of the application of, recent advanced in hybrid EAs in optimization.


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


Hui Li
Xidian University, China,