Differential Evolution Search Strategy Enhancement Through Evolutionary Game Theory. - Héctor Escobar-Cuevas; Erik Cuevas; Alberto Luque-Chang; Marco Pérez-Cisneros; Daniel Zaldivar 001; Oscar Barba-Toscano; Mario Vásquez; Nahum Aguirre; Eric L. Marin (CEC, 2024)

An advanced initialization technique for metaheuristic optimization: a fusion of Latin hypercube sampling and evolutionary behaviors. - Héctor Escobar-Cuevas; Erik Cuevas; Karla Avila; Omar Ávalos (Comput. Appl. Math., 2024)

A novel optimization approach based on unstructured evolutionary game theory. - Héctor Escobar-Cuevas; Erik Cuevas; Jorge Gálvez; Miguel Toski (Math. Comput. Simul., 2024)

A novel hybrid search strategy for evolutionary fuzzy optimization approach. - Héctor Escobar-Cuevas; Erik Cuevas; Jorge Gálvez; Karla Avila (Neural Comput. Appl., 2024)

Integration of metaheuristic operators through unstructured evolutive game theory approach: a novel hybrid methodology. - Héctor Escobar-Cuevas; Erik Cuevas; Jesús López; Marco Antonio Pérez Cisneros (Evol. Intell., 2025)

An improved swarm optimization algorithm using exploration and evolutionary game theory for efficient exploitation. - Nahum Aguirre; Erik Cuevas; Alberto Luque-Chang; Héctor Escobar-Cuevas (J. Supercomput., 2025)

Cellular neighbors optimizer: a novel metaheuristic approach inspired by the cellular automata and agent-based modeling for global optimization. - Oscar Barba-Toscano; Erik Cuevas; Héctor Escobar-Cuevas; Miguel Islas Toski (J. Supercomput., 2025)