Mario Alejandro Hevia Fajardo

According to our database, Mario Alejandro Hevia Fajardo authored at least 12 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

How Fitness Aggregation Methods Affect the Performance of Competitive CoEAs on Bilinear Problems.

Mario Alejandro Hevia Fajardo, Per Kristian Lehre

Algorithmica, September, 2025

2024

Self-adjusting offspring population sizes outperform fixed parameters on the cliff function.

Mario Alejandro Hevia Fajardo, Dirk Sudholt

Artif. Intell., March, 2024

Self-adjusting Population Sizes for Non-elitist Evolutionary Algorithms: Why Success Rates Matter.

Mario Alejandro Hevia Fajardo, Dirk Sudholt

Algorithmica, February, 2024

Ranking Diversity Benefits Coevolutionary Algorithms on an Intransitive Game.

Mario Alejandro Hevia Fajardo, Per Kristian Lehre

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

A Self-adaptive Coevolutionary Algorithm.

Mario Alejandro Hevia Fajardo, Erik Hemberg, Jamal Toutouh, Una-May O'Reilly, Per Kristian Lehre

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

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

Proceedings of the Genetic Programming Theory and Practice XX [GPTP 2023], 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

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Runtime Analysis of a Co-Evolutionary Algorithm: Overcoming Negative Drift in Maximin-Optimisation.

Mario Alejandro Hevia Fajardo, Per Kristian Lehre, Shishen Lin

Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023

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

Hard problems are easier for success-based parameter control.

Mario Alejandro Hevia Fajardo, Dirk Sudholt

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

2020

On the choice of the parameter control mechanism in the (1+(<i>λ, λ</i>)) genetic algorithm.

Mario Alejandro Hevia Fajardo, Dirk Sudholt

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

An empirical evaluation of success-based parameter control mechanisms for evolutionary algorithms.

Mario Alejandro Hevia Fajardo

Proceedings of the Genetic and Evolutionary Computation Conference, 2019