2024

• Gobert, M., Briffoteaux, G., Gmys, J., Melab, N., & Tuyttens, D. (November 2024). Observations in applying Bayesian versus evolutionary approaches and their hybrids in parallel time-constrained optimization. "Engineering Applications of Artificial Intelligence, 137", 109075. doi:10.1016/j.engappai.2024.109075
  • MGobert_EAAI.pdf
• Ducobu, F., Kugalur-Palanisamy, N., Briffoteaux, G., Gobert, M., Tuyttens, D., Arrazola, P.-J., & Rivière, E. (16 April 2024). Identification of the Constitutive and Friction Models Parameters via a Multi-Objective Surrogate-Assisted Algorithm for the Modeling of Machining—Application to Arbitrary Lagrangian Eulerian Orthogonal Cutting of Ti6Al4V. "Journal of Manufacturing Science and Engineering, 146" (6). doi:10.1115/1.4065223
  • Duco2024V_JMSE.pdf
• Briffoteaux, G., Melab, N., Mezmaz, M., & Tuyttens, D. (2024). Investigating surrogate-based hybrid acquisition processes. Application to Covid-19 contact mitigation. "Applied Soft Computing, 151", 111134. doi:10.1016/j.asoc.2023.111134
  • ASC2024.pdf

2022

• KUGALUR PALANISAMY, N., RIVIERE LORPHEVRE, E., Gobert, M., Briffoteaux, G., Tuyttens, D., Arrazola, P.-J., & DUCOBU, F. (06 June 2022). Identification of the Parameter Values of the Constitutive and Friction Models in Machining Using EGO Algorithm: Application to Ti6Al4V. "Metals, 12" (6), 976. doi:10.3390/met12060976
  • metals-12-00976-v2.pdf

• Briffoteaux, G., Ragonnet, R., Tomenko, P., Mezmaz, M., Melab, N., & Tuyttens, D. (2022). Comparing Parallel Surrogate-Based and Surrogate-Free Multi-objective Optimization of COVID-19 Vaccines Allocation. In B. Dorronsoro (Ed.), "Optimization and Learning - 5th International Conference, OLA 2022, Proceedings". Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-22039-5_16
  • OLA-Paper-2022.pdf
• Briffoteaux, G., Melab, N., Mezmaz, M., & Tuyttens, D. (2022). Hybrid Acquisition Processes in Surrogate-Based Optimization. Application to Covid-19 Contact Reduction. In M. Mernik & M. Črepinšek (Eds.), "Bioinspired Optimization Methods and Their Applications - 10th International Conference, BIOMA 2022, Proceedings". Springer Science and Business Media Deutschland GmbH. doi:10.1007/978-3-031-21094-5_10
  • BIOMA-Paper-2022.pdf

• Briffoteaux, G. (2022). "Parallel surrogate-based algorithms for solving expensive optimization problems" [Doctoral thesis, UMONS - Université de Mons]. ORBi UMONS-University of Mons. https://orbi.umons.ac.be/handle/20.500.12907/44381
  • g_briffoteaux_thesis.pdf

• Briffoteaux, G. (2022). "pySBO , Python platform for Surrogate-Based Optimization".

2021

• Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (2021). Evolution Control Ensemble Models for Surrogate-Assisted Evolutionary Algorithms. In "HPCS proceedings". IEEE.
  • g_briffoteaux_et_al.pdf

2020

• Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (22 July 2020). Evolution Control for parallel ANN-assisted simulation-based optimization: Application to Tuberculosis Transmission Control. "Future Generation Computer Systems, 113" (December 2020), 454-467. doi:10.1016/j.future.2020.07.005
  • article_FGCS_2019.pdf
• Briffoteaux, G., Gobert, M., Ragonnet, R., Gmys, J., Mezmaz, M., Melab, N., & Tuyttens, D. (2020). Parallel Surrogate-assisted Optimization: Batched Bayesian Neural Network-assisted GA versus q-EGO. "Swarm and Evolutionary Computation".

• Briffoteaux, G., Ragonnet, R., Mezmaz, M., Melab, N., & Tuyttens, D. (19 February 2020). "Towards Dynamic Selection of Evolution Controls in Parallel Bayesian Neural Network-assisted Genetic Algorithm" [Paper presentation]. International Conference on Optimization and Learning OLA'2020 17-19 February, Cadiz, Spain.
  • OLA20-guillaume_and_al.pdf

2018

• Briffoteaux, G., Melab, N., Mezmaz, M., & Tuyttens, D. (2018). An adaptive evolution control based on confident regions for surrogate-assisted optimization. In "2018 International Conference on High Performance Computing & Simulation, HPCS 2018, Orleans, France, July 16-20, 2018". IEEE. doi:10.1109/HPCS.2018.00130
  • HPCS2018.pdf