Harmony Search for Multi-objective Optimization. - Lucas M. Pavelski; Carolina P. de Almeida; Richard A. Gonçalves (SBRN, 2012)

ELMOEA/D-DE: Extreme Learning Surrogate Models in Multi-objective Optimization Based on Decomposition and Differential Evolution. - Lucas M. Pavelski; Myriam Regattieri Delgado; Carolina P. de Almeida; Richard A. Gonçalves; Sandra M. Venske (BRACIS, 2014)

A Hyper-Heuristic for the Environmental/Economic Dispatch Optimization Problem. - Richard A. Gonçalves; Carolina P. de Almeida; Sandra M. Venske; Josiel Neumann Kuk; Lucas M. Pavelski; Myriam Regattieri Delgado (BRACIS, 2015)

Adaptive Operator Selection in NSGA-III. - Richard A. Gonçalves; Carolina P. de Almeida; Lucas M. Pavelski; Sandra M. Venske; Josiel Neumann Kuk; Aurora T. R. Pozo (BRACIS, 2016)

Extreme Learning Surrogate Models in Multi-objective Optimization based on Decomposition. - Lucas M. Pavelski; Myriam Regattieri Delgado; Carolina P. de Almeida; Richard A. Gonçalves; Sandra M. Venske (Neurocomputing, 2016)

Adaptive Operator Selection for Many-Objective Optimization with NSGA-III. - Richard A. Gonçalves; Lucas M. Pavelski; Carolina P. de Almeida; Josiel Neumann Kuk; Sandra M. Venske; Myriam Regattieri Delgado (EMO, 2017)

Recommending Meta-Heuristics and Configurations for the Flowshop Problem via Meta-Learning: Analysis and Design. - Lucas Marcondes Pavelski; Marie-Eléonore Kessaci; Myriam Regattieri Delgado (BRACIS, 2018)

Meta-Learning for Optimization: A Case Study on the Flowshop Problem Using Decision Trees. - Lucas M. Pavelski; Myriam Regattieri Delgado; Marie-Eléonore Kessaci (CEC, 2018)

Meta-learning on flowshop using fitness landscape analysis. - Lucas Marcondes Pavelski; Myriam Regattieri Delgado; Marie-Eléonore Kessaci (GECCO, 2019)

Dynamic Learning in Hyper-Heuristics to Solve Flowshop Problems. - Lucas Marcondes Pavelski; Marie-Eléonore Kessaci; Myriam Regattieri Delgado (BRACIS (1), 2021)

Local Optima Network Sampling for Permutation Flowshop. - Lucas Marcondes Pavelski; Marie-Eléonore Kessaci; Myriam R. B. S. Delgado (CEC, 2021)

Flowshop NEH-Based Heuristic Recommendation. - Lucas Marcondes Pavelski; Marie-Eléonore Kessaci; Myriam Regattieri Delgado (EvoCOP, 2021)

An empirical analysis of constraint handling on evolutionary multi-objective algorithms for the Environmental/Economic Load Dispatch problem. - Josiel Neumann Kuk; Richard Aderbal Gonçalves; Lucas Marcondes Pavelski; Sandra Mara Guse Scós Venske; Carolina Paula de Almeida; Aurora Trinidad Ramirez Pozo (Expert Syst. Appl., 2021)

A Novel Multi-objective Decomposition Formulation for Per-Instance Configuration. - Lucas Marcondes Pavelski; Myriam Regattieri Delgado; Marie-Eléonore Kessaci (BRACIS (1), 2022)

An evolutionary search algorithm for efficient ResNet-based architectures: a case study on gender recognition. - André Ramos Fernandes Da Silva; Lucas Marcondes Pavelski; Luiz Alberto Queiroz Cordovil Júnior; Paulo Henrique De Oliveira Gomes; Layane Menezes Azevedo; Francisco Erivaldo Fernandes Junior (CEC, 2022)

An experience report on how remote device access tools helped mobile developers during the COVID-19 pandemic. - Hadassa Munguba Rabelo; Lucas Marcondes Pavelski; Eberth Felipe Castro da Cruz; Francisco Erivaldo Fernandes Junior (ICSSP/ICGSE, 2022)

A real-world case study for automated ticket team assignment using natural language processing and explainable models. - Lucas Marcondes Pavelski; Rodrigo de Souza Braga (ASE, 2022)

Hidden Design Principles in Zero-Cost Performance Predictors for Neural Architecture Search. - André Ramos Fernandes Da Silva; Lucas Marcondes Pavelski; Luiz Alberto Queiroz Cordovil Júnior (IJCNN, 2023)

Stochastic local search and parameters recommendation: a case study on flowshop problems. - Lucas M. Pavelski; Myriam Regattieri Delgado; Marie-Eléonore Kessaci; Alex Alves Freitas (Int. Trans. Oper. Res., 2023)