A Differential Mutation operator for the archive population of multi-objective evolutionary algorithms. - Lucas S. Batista; Frederico G. Guimarães; Jaime A. Ramírez (IEEE Congress on Evolutionary Computation, 2009)

A new self-adaptive approach for evolutionary multiobjective optimization. - Lucas S. Batista; Felipe Campelo; Frederico G. Guimarães; Jaime A. Ramírez (IEEE Congress on Evolutionary Computation, 2010)

A comparison of dominance criteria in many-objective optimization problems. - Lucas S. Batista; Felipe Campelo; Frederico G. Guimarães; Jaime A. Ramírez (IEEE Congress on Evolutionary Computation, 2011)

Pareto Cone ε-Dominance: Improving Convergence and Diversity in Multiobjective Evolutionary Algorithms. - Lucas S. Batista; Felipe Campelo; Frederico G. Guimarães; Jaime A. Ramírez (EMO, 2011)

Investigação de novas abordagens para otimização multiobjetivo em algoritmos evolutivos - Lucas S. Batista (2011)

Influence of relaxed dominance criteria in multiobjective evolutionary algorithms. - Fillipe Goulart; Lucas S. Batista; Felipe Campelo (GECCO (Companion), 2013)

An evolutionary approach for the demand side management optimization in smart grid. - Andre R. S. Vidal; Leonardo A. A. Jacobs; Lucas S. Batista (CIASG, 2014)

A distance based variable neighborhood search for parallel machine scheduling. - Andre Costa Batista; Lucas S. Batista (CIPLS, 2014)

A multiobjective robust controller synthesis approach aided by multicriteria decision analysis. - Wagner Eustaquio Gomes Bachur; Eduardo Nunes Gonçalves; Jaime Arturo Ramírez; Lucas S. Batista (Appl. Soft Comput., 2017)

The MOEADr Package - A Component-Based Framework for Multiobjective Evolutionary Algorithms Based on Decomposition. - Felipe Campelo; Lucas S. Batista; Claus Aranha (CoRR, 2018)

Demand Side Management using a multi-criteria ϵ-constraint based exact approach. - Andre Costa Batista; Lucas S. Batista (Expert Syst. Appl., 2018)

KDT-MOEA: A multiobjective optimization framework based on K-D trees. - Allysson S. M. Lacerda; Lucas S. Batista (Inf. Sci., 2019)

Natural gas pipeline network expansion under load-evolution uncertainty based on multi-criteria analysis. - Eduardo Santiago Ramos; Lucas S. Batista (Appl. Soft Comput., 2020)

The Cone epsilon-Dominance: An Approach for Evolutionary Multiobjective Optimization. - Lucas S. Batista; Felipe Campelo; Frederico G. Guimarães; Jaime A. Ramírez (CoRR, 2020)

A comparative study on surrogate models for SAEAs. - Mônica A. C. Valadão; Lucas S. Batista (Optim. Lett., 2020)

Improving proactive routing with a multicriteria and adaptive framework in ad-hoc wireless networks. - Jean N. R. Araujo; Lucas S. Batista; Claudio C. Monteiro (Wirel. Networks, 2020)

A Matheuristic Algorithm for the Multiple-Depot Vehicle and Crew Scheduling Problem. - Emiliana Mara Lopes Simões; Lucas S. Batista; Marcone Jamilson Freitas Souza (IEEE Access, 2021)

A diversity-driven migration strategy for distributed evolutionary algorithms. - Jean N. R. Araujo; Lucas S. Batista (Swarm Evol. Comput., 2023)

A multi-objective approach for manufacturing systems with multiple production routes based on supervisory control theory and heuristic algorithms. - Lucas V. R. Alves; Gustavo C. Rafael; Lucas S. Batista; Patrícia N. Pena (Discret. Event Dyn. Syst., 2023)

A model for optimal energy management in a microgrid using biogas. - Maria Izabel Santos; André L. Maravilha; Michel Bessani; Wadaed Uturbey; Lucas S. Batista (Evol. Intell., 2024)

Investigation of Kriging-based SAEAs' metamodel samples for computationally expensive optimization problems. - Mônica A. C. Valadão; André L. Maravilha; Lucas S. Batista (Evol. Intell., 2024)

EISPY2D: An Open-Source Python Library for the Development and Comparison of Algorithms in Two-Dimensional Electromagnetic Inverse Scattering Problems. - Andre Costa Batista; Ricardo Adriano; Lucas S. Batista (IEEE Access, 2025)

A self-tuning decomposition strategy in cooperative co-evolutionary algorithms for high-dimensional feature selection. - Pedro Vinícius A. B. de Venâncio; Lucas S. Batista (Knowl. Based Syst., 2025)

PyCCEA: A Python package of cooperative co-evolutionary algorithms for feature selection in high-dimensional data. - Pedro Vinícius A. B. de Venâncio; Lucas S. Batista (J. Open Source Softw., 2025)