Hybrid Techniques in Optimization


  • Dr. Adriana Lara
  • M. Sc. Lourdes Uribe

Set oriented methods have proven to be very efficient in the numerical treatment of various classes of global optimization problems in academy and industry and are widely used in many fields, such as Engineering and Finance. This special session serves as a platform for researchers from all over the world to present and discuss recent advances in set oriented numerical methods in particular in the context of optimization. Methods of this kind iterate (or evolve) entire sets instead of considering point-wise iterative methods and are thus in particular advantageous if a thorough investigation of the entire domain is required and/or the solution set is not given by a singleton.

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

  • Memetic Algorithms
  • Hybrid Metaheuristics
  • Hyperheuristics
  • Coupling heuristic/stochastic techniques with exact methods
  • Scalarization-based MOEAs
  • Interleaving of global approaches with local techniques
  • Two-phase algorithms

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


Contact: Dr. Adriana Lara This email address is being protected from spambots. You need JavaScript enabled to view it.

Short Bios:

  • Adriana Lara is a Full-Time Professor with the Mathematics Department of the Physics and Mathematics School (ESFM) at the IPN in México City. Her current research interests include Multi-objective Optimization, Hybrid Algorithms, and Data Analysis. She has received the IEEE Transactions on Evolutionary Computation Outstanding Paper Award in 2010 and 2012; also the 2010 Engineering Award granted by the Mexico City's Science and Technology Institute (ICyTDF). She received the B.Sc. degree in Physics and Mathematics from the National Polytechnic Institute (IPN), in Mexico City; the M.Sc. degree in Electrical Engineering and the Ph.D. degree inComputer Sciences from Centro de Investigación y Estudios Avanzados
  • Lourdes Uribe obtained his B.S. in mathematics from the ESFM-IPN in 2013 and his M.S. in Physical-mathematical Science from ESFM-IPN 2015. She is currently a Ph.D student in ESFM-IPN. Her areas of interest are the multi-objective optimization, gradient based techniques, as well as hybrid algorithms.