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Rafael de Carvalho Miranda
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2020 – today
- 2024
- [j14]João Victor Soares do Amaral, José Arnaldo Barra Montevechi, Rafael de Carvalho Miranda, Carlos Henrique dos Santos:
Adaptive metamodeling simulation optimization: Insights, challenges, and perspectives. Appl. Soft Comput. 165: 112067 (2024) - [j13]André Aoun Montevechi, Rafael de Carvalho Miranda
, André Luiz Medeiros
Advancing credit risk modelling with Machine Learning: A comprehensive review of the state-of-the-art. Eng. Appl. Artif. Intell. 137: 109082 (2024) - [j12]Aneirson Francisco da Silva
A new multiple criteria data envelopment analysis with variable return to scale: Applying bi-dimensional representation and super-efficiency analysis. Eur. J. Oper. Res. 314(1): 308-322 (2024) - [j11]Carlos Henrique dos Santos
Digital Twin simulation models: a validation method based on machine learning and control charts. Int. J. Prod. Res. 62(7): 2398-2414 (2024) - 2023
- [c3]José Arnaldo Barra Montevechi, João Victor Soares do Amaral, Rafael de Carvalho Miranda, Carlos Henrique dos Santos, Flavio Oliveira de Brito, Michael E. F. H. S. Machado:
Ensemble-Based Infill Search Simulation Optimization Framework. WSC 2023: 3059-3070 - 2022
- [j10]Aneirson Francisco da Silva
Goal programming and multiple criteria data envelopment analysis combined with optimization and Monte Carlo simulation: An application in railway components. Expert Syst. J. Knowl. Eng. 39(2) (2022) - [j9]Carlos Henrique dos Santos
Decision support in productive processes through DES and ABS in the Digital Twin era: a systematic literature review. Int. J. Prod. Res. 60(8): 2662-2681 (2022) - [j8]João Victor Soares do Amaral
Metamodel-based simulation optimization: A systematic literature review. Simul. Model. Pract. Theory 114: 102403 (2022) - 2021
- [j7]Tábata Fernandes Pereira
Application of a management and storage system for knowledge generated from simulation projects as a teaching and assessment tool. Simul. 97(12) (2021) - 2020
- [j6]Fernando Augusto Silva Marins
A new approach using fuzzy DEA models to reduce search space and eliminate replications in simulation optimization problems. Expert Syst. Appl. 144: 113137 (2020) - [j5]Wilson Trigueiro de Sousa Junior
Shop floor simulation optimization using machine learning to improve parallel metaheuristics. Expert Syst. Appl. 150: 113272 (2020)
2010 – 2019
- 2019
- [j4]Wilson Trigueiro de Sousa Junior
Discrete simulation-based optimization methods for industrial engineering problems: A systematic literature review. Comput. Ind. Eng. 128: 526-540 (2019) - 2017
- [j3]Rafael de Carvalho Miranda
Increasing the efficiency in integer simulation optimization: Reducing the search space through data envelopment analysis and orthogonal arrays. Eur. J. Oper. Res. 262(2): 673-681 (2017) - [j2]José Arnaldo Barra Montevechi, Rafael Florencio da Silva Costa, Alexandre Ferreira de Pinho
A simulation-based approach to perform economic evaluation scenarios. J. Simulation 11(2): 185-192 (2017) - 2015
- [j1]Tábata Fernandes Pereira, José Arnaldo Barra Montevechi, Rafael de Carvalho Miranda
Integrating soft systems methodology to aid simulation conceptual modeling. Int. Trans. Oper. Res. 22(2): 265-285 (2015) - [c2]José Arnaldo Barra Montevechi, Tábata Fernandes Pereira, Carlos Eduardo Sanches da Silva
Identification of the main methods used in simulation projects. WSC 2015: 3469-3480 - 2013
- [c1]José Arnaldo Barra Montevechi, Fabiano Leal
Interactive learning of modeling and discrete-events simulation through Lego® parts. WSC 2013: 3556-3567
Coauthor Index
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