A new proposal to hybridize the Nelder-Mead method to a differential evolution algorithm for constrained optimization. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (IEEE Congress on Evolutionary Computation, 2009)

Solving multi-objective optimization problems using differential evolution and a maximin selection criterion. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (IEEE Congress on Evolutionary Computation, 2012)

A new selection mechanism based on hypervolume and its locality property. - Adriana Menchaca-Méndez; Carlos Artemio Coello Coello (IEEE Congress on Evolutionary Computation, 2013)

Selection Operators Based on Maximin Fitness Function for Multi-Objective Evolutionary Algorithms. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (EMO, 2013)

MD-MOEA : A new MOEA based on the maximin fitness function and Euclidean distances between solutions. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (IEEE Congress on Evolutionary Computation, 2014)

A More Efficient Selection Scheme in iSMS-EMOA. - Adriana Menchaca-Méndez; Elizabeth Montero; María Cristina Riff; Carlos A. Coello Coello (IBERAMIA, 2014)

MH-MOEA: A New Multi-Objective Evolutionary Algorithm Based on the Maximin Fitness Function and the Hypervolume Indicator. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (PPSN, 2014)

GDE-MOEA: A new MOEA based on the Generational Distance indicator and ε-dominance. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (CEC, 2015)

GD-MOEA: A New Multi-Objective Evolutionary Algorithm Based on the Generational Distance Indicator. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (EMO (1), 2015)

Δp-MOEA: A new multi-objective evolutionary algorithm based on the Δp indicator. - Adriana Menchaca-Méndez; Carlos Ignacio Hernandez Castellanos; Carlos A. Coello Coello (CEC, 2016)

Selection mechanisms based on the maximin fitness function to solve multi-objective optimization problems. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (Inf. Sci., 2016)

An alternative hypervolume-based selection mechanism for multi-objective evolutionary algorithms. - Adriana Menchaca-Méndez; Carlos A. Coello Coello (Soft Comput., 2017)

An Improved S-Metric Selection Evolutionary Multi-Objective Algorithm With Adaptive Resource Allocation. - Adriana Menchaca-Méndez; Elizabeth Montero; Saúl Zapotecas Martínez (IEEE Access, 2018)

A Co-Evolutionary Scheme for Multi-Objective Evolutionary Algorithms Based on $ epsilon$ -Dominance. - Adriana Menchaca-Méndez; Elizabeth Montero; Luis Miguel Antonio; Saúl Zapotecas Martínez; Carlos A. Coello Coello; María Cristina Riff (IEEE Access, 2019)

On the Performance of Generational and Steady-State MOEA/D in the Multi-Objective 0/1 Knapsack Problem. - Saúl Zapotecas Martínez; Adriana Menchaca-Méndez (CEC, 2020)

An algorithm to compute time-balanced clusters for the delivery logistics problem. - Adriana Menchaca-Méndez; Elizabeth Montero; Marisol Flores-Garrido; Luis Miguel Antonio (Eng. Appl. Artif. Intell., 2022)

Uniform mixture design via evolutionary multi-objective optimization. - Adriana Menchaca-Méndez; Saúl Zapotecas Martínez; Luis Miguel García-Velázquez; Carlos A. Coello Coello (Swarm Evol. Comput., 2022)

An Archive-Based Multi-Objective Simulated Annealing Algorithm for the Time/Weight-Balanced Cluster Problem in Delivery Logistics. - Eduardo Manuel Ceja-Cruz; Adriana Menchaca-Méndez; Elizabeth Montero; Saúl Zapotecas Martínez (CEC, 2023)

Engineering applications of multi-objective evolutionary algorithms: A test suite of box-constrained real-world problems. - Saúl Zapotecas Martínez; Abel García-Nájera; Adriana Menchaca-Méndez (Eng. Appl. Artif. Intell., 2023)