Abstract
Tabu Search is a metaheuristic renowned for its ability to navigate complex solution spaces by iteratively exploring neighborhoods and intelligently diversifying the search process to avoid getting trapped in local optima. We describe the main elements of the tabu search methodology in the context of finding high-quality solutions to the minimum dominating set problem (MDSP). The MDSP is a fundamental combinatorial optimization challenge with applications in various fields, including network design, social network analysis, and bioinformatics.
J. Manuel Colmenar
Full Professor
My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.
