Hyper Heuristics for Optimization

Chair: Dr. Octavio Ramos-Figueroa

Hyper-heuristic algorithms arise as a proposal to automate the design of optimization algorithms. The methods designed under this approach have a more general vision, i.e., they use search heuristic strategies that can be effective in different problems that share certain characteristics and properties to seek a certain degree of generality. A hyper-heuristic operates with a high-level (meta-)heuristic in charge of determining the best way to select, combine, or adapt different low-level (meta-)heuristics to solve a family of problems. This special session serves as a platform for researchers from all over the world to present and discuss recent advances and perspectives in hyper-heuristic algorithms for optimization.

 

Topics of interest include (but are not limited to):

  • continuous and combinatorial optimization
  • single-objective and multi-objective problems
  • bi-level optimization
  • hyperheuristics without learning
  • hyper heuristics with online and offline learning
  • hyper heuristics based on selection, generation, sequencing, and machine learning
  • hyper hueristics with low-level heurístics, metahueristics, and memetic algorithms
  • hyper heuristics with construction and perturbation heuristics
  • Hyper heuristics for single or multiple benchmarks for a single problem
  • Hyper heuristics for several problems of single or multiple domains

 

All submission will be peer-reviewed by a panel of international experts.

Contact: Dr. Octavio Ramos-Figueroa

 

 

 
Octavio Ramos-Figueroa holds a postdoctoral position at the Artificial Intelligence Research Institute at Universidad Veracruzana (IIIA-UV) in Xalapa City, Mexico. His research interests include: continuous and combinatorial optimization, experimental study of metaheuristic and hyper heuristic algorithms, characterization, data mining, and data science pipelines. He received his Ph.D. and the degree of master in Artificial Intelligence from the Artificial Intelligence Research Institute at the Universidad Veracruzana, Mexico. He studied engineering in information and communications technologies at the Instituto Tecnológico de Tepic, Mexico. He is a member of the Mexican National Researchers System (SNI)