3 citations · 5 across the 14 of their papers we have counts for
17 papers · 1 filter
Feedback approaches for set-point stabilization of interacting particle systems
Daniel Jannik Happ, Birgit Jacob, Claudia Totzeck
We explore the problem of asymptotically stabilizing a class of interacting particle systems to a prescribed particle configuration with zero velocity. The class of interacting par…
A Consensus-based optimization algorithm using Gaussian processes for global optimization problems in Sobolev spaces
Mahmoud Khatab, Claudia Totzeck
We propose an algorithm to approximate solutions of global optimization problems in Sobolev spaces that follows the spirit of Consensus-based algorithms in finite dimensions. The m…
CBX: Python and Julia packages for consensus-based interacting particle methods
Rafael Bailo, Alethea Barbaro, Susana N. Gomes +4
We introduce CBXPy and ConsensusBasedX.jl, Python and Julia implementations of consensus-based interacting particle systems (CBX), which generalise consensus-based optimization met…
Kinetic based optimization enhanced by genetic dynamics
Giacomo Albi, Federica Ferrarese, Claudia Totzeck
We propose and analyse a variant of the recently introduced kinetic based optimization method that incorporates ideas like survival-of-the-fittest and mutation strategies well-know…
Modeling Minimum Cost Network Flows With Port-Hamiltonian Systems
Onur Tanil Doganay, Kathrin Klamroth, Bruno Lang +2
We give a short overview of advantages and drawbacks of the classical formulation of minimum cost network flow problems and solution techniques, to motivate a reformulation of clas…
A new perspective on dynamic network flow problems via port-Hamiltonian systems
Onur Tanil Doganay, Kathrin Klamroth, Bruno Lang +2
We suggest a global perspective on dynamic network flow problems that takes advantage of the similarities to port-Hamiltonian dynamics. Dynamic minimum cost flow problems are formu…