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Research Interest in: Bilevel optimization, Global Optimization, Evolutionary Computation, Automated Parameter Tuning and Machine Learning. https://bi-level.org
This work presents a study about a special class of infeasible solutions called here as pseudo-feasible solutions in bilevel optimization. This work is focused on determining how such solutions can affect the performance of an evolutionary algorithm. After its formal definition, and based on theoretical results, two conditions to detect and deal wi...
This work presents a proposal for the automated parameter tuning problem (APTP) modeled as a bilevel optimization problem. Different definitions and theoretical results are given in order to formalize the APTP in the context of this hierarchical optimization problem. The obtained bilevel optimization problem is solved via a population-based algorit...
Physical phenomena have been the inspiration for proposing different optimization methods such as electro-search algorithm, central force optimization, and charged system search among others. This work presents a new optimization algorithm based on some principles from physics and mechanics, which is called Evolutionary Centers Algorithm (ECA). We...
Design of a version of the ECA algorithm to solve bilevel optimization problems with competitive results and with a lower number of evaluations than metaheuristic algorithms of the state of the art.