Speakers - Carlos Hernández

Cell Mapping Methods for Multi-objective Optimization
Carlos Hernández
Mutuo Financiera

Talk Abstract: In the last decades there has been an increased interest to solve multi-objective optimization problems. This kind of problems appear in almost every aspect of life, since it is typical to have several objectives that are in conflict. The focus of the area is to find one or several best trade-off solutions (that form the so-called global Pareto set/front). Most state-of-the-art algorithms aim to find an approximation of these sets. However, in most of the cases they do not give further information about the problem. In this talk, we will focus on the design and study of the cell mapping methods. Such methods are capable to exploit information such as basins of attraction, local optimal solutions and neighborhood information. This information is useful to compute different sets of interest for the decision maker besides the global Pareto set/front. These sets include the local Pareto set/front and the set of nearly optimal solutions which can be useful as backup solutions. Further, the set of lightly robust optimal solutions which is in particular important when the problems are subject to uncertainties. We will highlight the usefulness of the cell mapping methods in several real world applications from optimal control. Finally, we will discuss future directions of the cell mapping for problems with uncertainty.

Bio: Carlos was born in Tepic Nayarit. He started his academical career in the Instituto Tecnológico de Tepic. Later he studied his masters at CINVESTAV-IPN for which he obtained the award for the best thesis in artificial intelligence by the Mexican Society of Artificial Intelligence. In 2017, he obtained his Ph.D. at CINVESTAV-IPN for which he obtained the Rosenblueth Award. Currently, he is CTO and co-founder at Mutuo Financiera. His primary research topics include set oriented numerics, multi-objective optimization, and optimization under uncertainty.