An empirical evaluation of success-based parameter control mechanisms for evolutionary algorithms. - Mario Alejandro Hevia Fajardo (GECCO, 2019)

On the choice of the parameter control mechanism in the (1+(λ, λ)) genetic algorithm. - Mario Alejandro Hevia Fajardo; Dirk Sudholt (GECCO, 2020)

Hard problems are easier for success-based parameter control. - Mario Alejandro Hevia Fajardo; Dirk Sudholt (GECCO, 2022)

Theoretical and Empirical Analysis of Parameter Control Mechanisms in the (1 + (λ, λ)) Genetic Algorithm. - Mario Alejandro Hevia Fajardo; Dirk Sudholt (ACM Trans. Evol. Learn. Optim., 2022)

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre; Shishen Lin (FOGA, 2023)

Analysis of a Pairwise Dominance Coevolutionary Algorithm And DefendIt. - Per Kristian Lehre; Mario Alejandro Hevia Fajardo; Jamal Toutouh; Erik Hemberg; Una-May O'Reilly (GECCO, 2023)

Analysis of a Pairwise Dominance Coevolutionary Algorithm with Spatial Topology. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre; Jamal Toutouh; Erik Hemberg; Una-May O'Reilly (GPTP, 2023)

A Self-adaptive Coevolutionary Algorithm. - Mario Alejandro Hevia Fajardo; Erik Hemberg; Jamal Toutouh; Una-May O'Reilly; Per Kristian Lehre (GECCO, 2024)

Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre (PPSN (3), 2024)

Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: Why Success Rates Matter. - Mario Alejandro Hevia Fajardo; Dirk Sudholt (Algorithmica, 2024)

Self-adjusting offspring population sizes outperform fixed parameters on the cliff function. - Mario Alejandro Hevia Fajardo; Dirk Sudholt (Artif. Intell., 2024)

How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems. - Mario Alejandro Hevia Fajardo; Per Kristian Lehre (Algorithmica, 2025)