Offices
Graduiertenkolleg EDDy:
Pontdriesch 14, bldg 1953, room 257
IGPM: Templergraben 55, bldg 1010, room 126.2
Postal Address
RWTH Aachen University, Math 111810,
Templergraben 55, 52062 Aachen
Phone
+49 241 80 93067
borghi AT eddy DOT rwth-aachen DOT de
Research Area
Kinetic theory for swarm-based optimization methods
Supervisors
Michael Herty, Manuel Torrilhon, and Lorenzo Pareschi
Publications
Binary interaction methods for high dimensional global optimization and machine learning
A. Benfenati, G. Borghi, and L. Pareschi
Appl. Math. Optim. 86 (2022), no. 1, Paper No. 9
doi: 10.1007/s00245-022-09836-5
Preprint arXiv:2105.02695Constrained consensus-based optimization
G. Borghi, M. Herty, and L. Pareschi
SIAM J. Optim. 33 (2023), no. 1, 211–236
doi: 10.1137/22M1471304
Preprint arXiv:2111.10571A consensus-based algorithm for multi-objective optimization and its mean-field description
G. Borghi, M. Herty, and L. Pareschi
2022 IEEE 61st Conference on Decision and Control (CDC), Cancun, Mexico, 2022, pp. 4131-4136
doi: 10.1109/CDC51059.2022.9993095
Preprint arXiv:2203.16384An adaptive consensus based method for multi-objective optimization with uniform Pareto front approximation
G. Borghi, M. Herty, and L. Pareschi
Appl Math Optim 88, 58 (2023)
doi: 10.1007/s00245-023-10036-y
Preprint arXiv:2208.01362Repulsion dynamics for uniform Pareto front approximation in multi-objective optimization problems
G. Borghi
PAMM, Vol. 23, Issue 1 e202200285
doi: 10.1002/pamm.202200285
Preprint arXiv.2211.03378Consensus based optimization with memory effects: Random selection and applications
G. Borghi, S. Grassi, and L. Pareschi
Chaos, Solitons & Fractals, Vol. 174, 2023, 113859
doi: 10.1016/j.chaos.2023.113859Kinetic description and convergence analysis of genetic algorithms for global optimization
G. Borghi and L. Pareschi
Preprint arXiv:2310.08562Model predictive control strategies using consensus-based optimization
G. Borghi and M. Herty
Preprint arXiv:2312.13085