Lucas M. Pavelski

According to our database, Lucas M. Pavelski authored at least 19 papers between 2012 and 2023.

Collaborative distances:

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

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

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

Proceedings of the International Joint Conference on Neural Networks, 2023

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

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering, 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

Proceedings of the ICSSP/ICGSE 2022: 16th International Conference on Software and System Processes and 17th International Conference on Global Software Engineering, Virtual Event / Pittsburgh, PA, USA, May 19, 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

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

A Novel Multi-objective Decomposition Formulation for Per-Instance Configuration.

Lucas Marcondes Pavelski, Myriam Regattieri Delgado, Marie-Eléonore Kessaci

Proceedings of the Intelligent Systems - 11th Brazilian Conference, 2022

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

Flowshop NEH-Based Heuristic Recommendation.

Lucas Marcondes Pavelski, Marie-Eléonore Kessaci, Myriam Regattieri Delgado

Proceedings of the Evolutionary Computation in Combinatorial Optimization, 2021

Local Optima Network Sampling for Permutation Flowshop.

Lucas Marcondes Pavelski, Marie-Eléonore Kessaci, Myriam R. B. S. Delgado

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

Dynamic Learning in Hyper-Heuristics to Solve Flowshop Problems.

Lucas Marcondes Pavelski, Marie-Eléonore Kessaci, Myriam Regattieri Delgado

Proceedings of the Intelligent Systems - 10th Brazilian Conference, 2021

2019

Meta-learning on flowshop using fitness landscape analysis.

Lucas Marcondes Pavelski, Myriam Regattieri Delgado, Marie-Eléonore Kessaci

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

2018

Meta-Learning for Optimization: A Case Study on the Flowshop Problem Using Decision Trees.

Lucas M. Pavelski, Myriam Regattieri Delgado, Marie-Eléonore Kessaci

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

Recommending Meta-Heuristics and Configurations for the Flowshop Problem via Meta-Learning: Analysis and Design.

Lucas Marcondes Pavelski, Marie-Eléonore Kessaci, Myriam Regattieri Delgado

Proceedings of the 7th Brazilian Conference on Intelligent Systems, 2018

2017

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

Proceedings of the Evolutionary Multi-Criterion Optimization, 2017

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 in NSGA-III.

Richard A. Gonçalves, Carolina P. de Almeida, Lucas M. Pavelski, Sandra M. Venske, Josiel Neumann Kuk, Aurora T. R. Pozo

Proceedings of the 5th Brazilian Conference on Intelligent Systems, 2016

2015

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

Proceedings of the 2015 Brazilian Conference on Intelligent Systems, 2015

2014

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

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2012

Harmony Search for Multi-objective Optimization.

Lucas M. Pavelski, Carolina P. de Almeida, Richard A. Gonçalves

Proceedings of the 2012 Brazilian Symposium on Neural Networks, 2012